Cloud-based motor monitoring as a service is revolutionizing the way industries manage and maintain their critical assets. By leveraging the power of the cloud, organizations can remotely monitor motors, analyze performance data, and predict potential failures. However, as this technology continues to evolve, several challenges emerge that need to be addressed for successful implementation and operation. In this blog post, we will explore the top challenges faced in cloud-based motor monitoring as a service in 2023. 

Data Security and Privacy:

One of the primary concerns in cloud-based motor monitoring is ensuring the security and privacy of sensitive data. As motor data is transmitted and stored in the cloud, there is a need for robust encryption, authentication, and access control mechanisms. In 2023, organizations will face the challenge of implementing comprehensive data security measures to protect against unauthorized access, data breaches, and potential cyber threats. Compliance with data privacy regulations, such as GDPR or CCPA, adds an additional layer of complexity to this challenge.

Connectivity and Network Reliability:

For effective motor monitoring, a reliable and secure network connection is crucial. In remote or industrial environments, ensuring continuous connectivity can be challenging. Factors such as signal strength, network coverage, and bandwidth limitations need to be addressed to enable real-time data transmission and analysis. Organizations in 2023 will need to deploy robust networking infrastructure, explore alternative connectivity options like satellite or cellular networks, and implement redundancy measures to mitigate the risk of network disruptions.

Scalability and Data Management:

Cloud-based motor monitoring generates vast amounts of data that need to be efficiently processed, stored, and analyzed. In 2023, as the number of monitored motors increases, organizations will face challenges in scaling their data management infrastructure. They will need to ensure that their cloud-based systems can handle the growing volume of data, implement efficient data storage and retrieval mechanisms, and utilize advanced analytics and machine learning techniques to extract meaningful insights from the data.

Integration with Existing Systems:

Integrating cloud-based motor monitoring systems with existing infrastructure and software can pose significant challenges. In 2023, organizations will need to ensure seamless integration with their existing enterprise resource planning (ERP), maintenance management, and asset management systems. This includes establishing data pipelines, defining standardized protocols, and implementing interoperability between different systems. Compatibility with various motor types, brands, and communication protocols also adds complexity to the integration process.

Cost and Return on Investment:

While cloud-based motor monitoring offers numerous benefits, organizations must carefully evaluate the cost implications and expected return on investment (ROI). Implementing and maintaining the necessary hardware, software, and cloud infrastructure can incur significant expenses. Organizations in 2023 will face the challenge of assessing the financial viability of cloud-based motor monitoring, considering factors such as deployment costs, ongoing operational expenses, and the potential savings achieved through improved motor performance, reduced downtime, and optimized maintenance schedules.

Connectivity and Reliability:

Cloud-based motor monitoring relies heavily on stable and reliable internet connectivity. However, in certain remote locations or industrial settings, maintaining a consistent connection can be challenging. The availability of high-speed internet, network outages, or intermittent connections may impact real-time monitoring and timely data transmission. Service providers will need to address connectivity issues to ensure uninterrupted monitoring and minimize potential disruptions.

Scalability and Performance:

As the number of monitored motors increases, scalability and performance become critical challenges. Service providers must design their cloud infrastructure to handle the growing volume of data generated by motor sensors. Ensuring real-time data processing, analytics, and insights at scale will be vital to meet the demands of large-scale motor monitoring deployments. Continuous optimization and proactive capacity planning will be necessary to maintain optimal performance levels.

Integration with Legacy Systems:

Integrating cloud-based motor monitoring with existing legacy systems can be a complex undertaking. Many organizations have legacy equipment or infrastructure that may not be inherently compatible with cloud-based solutions. The challenge lies in seamlessly integrating these disparate systems to enable data exchange and unified monitoring. Service providers need to offer flexible integration options, standardized protocols, and compatibility with a wide range of motor types and manufacturers.

Data Analytics and Actionable Insights:

Collecting data from motor sensors is only the first step. The real value lies in extracting actionable insights from this data to enable predictive maintenance, identify performance trends, and optimize motor operations. Service providers must develop advanced analytics capabilities that can process large volumes of motor data and provide meaningful insights in a user-friendly format. The challenge is to offer intuitive dashboards, anomaly detection, and predictive analytics that empower users to make data-driven decisions effectively.

Conclusion:

Cloud-based motor monitoring as a service offers tremendous potential for organizations seeking to optimize motor performance and maintenance. However, in 2023, several challenges need to be addressed to ensure its successful implementation. From data security and connectivity issues to scalability, integration, and advanced analytics, service providers must actively tackle these challenges to unlock the full benefits of cloud-based motor monitoring. By doing so, organizations can enhance operational efficiency, extend motor lifespan, and reduce costly downtime in the ever-evolving landscape of motor-driven industries.

We all know how IoT has revolutionized the way we interact with the world. IoT devices are now ubiquitous, from smart homes to industrial applications. A significant portion of these devices are Wireless Sensor Networks (WSNs), which are a key component of IoT systems. However, designing and implementing WSNs presents several challenges for embedded engineers. In this article, we discuss some of the significant challenges that embedded engineers face when working with WSNs.

WSNs are a network of small, low-cost, low-power, and wirelessly connected sensor nodes that can sense, process, and transmit data. These networks can be used in a wide range of applications such as environmental monitoring, healthcare, industrial automation, and smart cities. WSNs are typically composed of a large number of nodes, which communicate with each other to gather and exchange data. The nodes are equipped with sensors, microprocessors, transceivers, and power sources. The nodes can also be stationary or mobile, depending on the application.

One of the significant challenges of designing WSNs is the limited resources of the nodes. WSNs are designed to be low-cost, low-power, and small, which means that the nodes have limited processing power, memory, and energy. This constraint limits the functionality and performance of the nodes. Embedded engineers must design WSNs that can operate efficiently with limited resources. The nodes should be able to perform their tasks while consuming minimal power to maximize their lifetime.

Another challenge of WSNs is the limited communication range. The nodes communicate with each other using wireless radio signals. However, the range of the radio signals is limited, especially in indoor environments where the signals are attenuated by walls and other obstacles. The communication range also depends on the transmission power of the nodes, which is limited to conserve energy. Therefore, embedded engineers must design WSNs that can operate reliably in environments with limited communication range.

WSNs also present a significant challenge for embedded engineers in terms of data management. WSNs generate large volumes of data that need to be collected, processed, and stored. However, the nodes have limited storage capacity, and transferring data to a centralized location may not be practical due to the limited communication range. Therefore, embedded engineers must design WSNs that can perform distributed data processing and storage. The nodes should be able to process and store data locally and transmit only the relevant information to a centralized location.

Security is another significant challenge for WSNs. The nodes in WSNs are typically deployed in open and unprotected environments, making them vulnerable to physical and cyber-attacks. The nodes may also contain sensitive data, making them an attractive target for attackers. Embedded engineers must design WSNs with robust security features that can protect the nodes and the data they contain from unauthorized access.

The deployment and maintenance of WSNs present challenges for embedded engineers. WSNs are often deployed in harsh and remote environments, making it difficult to access and maintain the nodes. The nodes may also need to be replaced periodically due to the limited lifetime of the power sources. Therefore, embedded engineers must design WSNs that are easy to deploy, maintain, and replace. The nodes should be designed for easy installation and removal, and the network should be self-healing to recover from node failures automatically.

Final thought; WSNs present significant challenges for embedded engineers, including limited resources, communication range, data management, security, and deployment and maintenance. Addressing these challenges requires innovative design approaches that can maximize the performance and efficiency of WSNs while minimizing their cost and complexity. Embedded engineers must design WSNs that can operate efficiently with limited resources, perform distributed data processing and storage, provide robust security features, and be easy to deploy

Some say that if World War III breaks out, it will be fought in cyberspace. As IoT systems gather more and more under the “umbrella” of the network, security has never been more important to various user groups. From the traffic lights that play an important role in our urban traffic to the power system that provides energy for them, to the management and monitoring systems that keep cars running well, security in the use of networks and devices has become the basis and basis of modern communication devices and systems. necessary condition. Providing solid security in the online world is no easy task. Security is one of the very few scientific and technological means that must be confronted with external forces to achieve overdue results. What is more complicated is that these external forces can break through the defense line time after time through traditional and innovative means. Because of the many potential attack methods, information and network security has become an attractive and challenging topic, which is closely related to enterprises, industries and life.

For decades, the information technology (IT) environment has been very active and the hardest hit area for attacks and threats, which has also allowed IT to grow rapidly. In contrast, the operational technology (OT) environment is relatively traditional and closed, and the connection methods and channels between devices and the network are very limited. Therefore, compared with IT, OT records relatively fewer attack events, but its learning opportunities Countermeasures are also relatively scarce. But security in the OT world tends to have a broader security scope than IT. For example, in OT, security is almost equivalent to safety. In fact, the connected security standards of IIoT also incorporate the safety of equipment and people. This installment will focus on common challenges facing OT security.

The erosion problem of network architecture. The main issues facing the protection of industrial environments are initial design and ongoing maintenance. The original design concept stems from a premise that the network itself is safe, because it is isolated on the physical level of the enterprise, with little or no connection with the external environment, and the attacker lacks sufficient correlation knowledge to perform security attacks. In the vast majority of cases, the initial network design is sound, even good practice and relative standards. But in fact, from the point of view of security design, it is better to cope with the growing demand than to conceal the lack of communication and improve the response. It is relatively common that, over time, an otherwise hidden problem may be exposed by temporary updates and cracks to the hardware, allowing the problem to go unchecked and spread across the entire device family leading to a complete network and system crash Case.

Pervasive system legacy issues. In an industrial environment, the span of new and old equipment is large, the equipment life cycle is long, and the operating system of the equipment is not uniform enough, which makes the maintenance of the equipment extremely troublesome, and also exposes security issues such as system vulnerabilities. For example, in the context of urban power systems, it is not uncommon for older mechanical equipment to intersect with modern smart electronics. For the legacy components, because the old equipment cannot be connected to the network, the equipment is encouraged to run, but the entire system is integrated into the network, and some conditions cannot be monitored. From a security point of view, this situation is a potential threat, because many devices are likely to be unpatched or have vulnerabilities due to legacy issues, and it is more likely that the corresponding solutions for devices that are aging due to the passage of time cannot be applied. Therefore, we should strengthen the management of patches and devices, generate corresponding tools, and protect the vulnerabilities that may be exploited as much as possible.

Unsafe operating protocol. Among industrial control protocols, especially those based on serial ports, they are only considered for communication at the beginning of design, and there is no relative requirement for security. This has become the weakness and inherent loophole of the current network transmission protocol. In addition, the security considerations in the embedded operating system are relatively lacking. In old industrial protocols, data protocols such as monitoring and data acquisition often have coexisting security issues. Including the lack of communication authentication, static and dynamic data cannot establish effective protection, which makes the data in transmission often public. Although the data may not be so important, the risk of data tampering must be prevented.

The device is not secure. In addition to the defects of the communication protocol, the control equipment and the communication components themselves also have loopholes and defects. Before 2010, the world paid little attention to the security of industrial design, which also led to the fact that industrial design did not undergo the fire-zero test like IT, which led to frequent occurrence of vulnerability-related problems in the industry. This also reminds the OT industry to pay attention to the safety of the equipment itself.
IoT security issues are often more than that, including supplier dependence, security knowledge presentation and demonstration issues, etc. All these aspects remind the importance of safety all the time.

In recent days, neural networks have become a topic for discussion. But the question still needs to be solved- How can it affect our world today and tomorrow?

The global neural network market's compound annual growth rate (CAGR) is expected to be 26.7% from 2021 to 2030. This means that new areas of application for them might appear soon. The Internet of Things that is IoT, is today's most fascinating and required technological solution for business. Around 61% of companies utilize IoT platforms, and we can anticipate the integration of neural networks into enterprise IoT solutions. This anticipation raises many questions, like what gets such collaboration and how to prepare it. Can we optimize the IoT ecosystem using neural networks, and who will approach such solutions?

What do you understand by a neural network, and how is it beneficial for enterprise IoT?

An artificial neural network that is ANN is a network of artificial neurons striving to simulate the analytical mechanisms taken by the human brain. This type of artificial intelligence includes a range of algorithms that can "learn" from their own experience and improve themselves, which is very different from classical algorithms that are programmed to resolve only specific tasks. Thus, with time, the neural network will remain pertinent and keep on improving.

With the proper implementation, enterprise internet of things (EIoT) and ANN can offer the business the most valuable things: precise analytics and forecasts. In general, it is not possible to compare both. Enterprise IoT is a system that needs software for data analysis, whereas ANN is a component that needs a large amount of data to be operational. Their team naturally controls the analytical tasks; therefore, high-level business tasks are performed most effectively, reducing costs, automating processes, finding new revenue sources, etc.

In the Internet of Things ecosystem, neural networks help in two areas above all:

• Data acquisition via ANN-based machine vision
• Advanced-data analysis

If it needs significant investments to execute ANN in big data analytics solutions, neural network image processing can decrease the cost of the IoT solution. Thus, neural networks improve enterprise IoT solutions, enhance their value, and speed up global adoption.

Which solutions within enterprise IoT can be enhanced using neural networks?

IoT-based visual control

The IoT ecosystem begins with data collection. Data quality impacts the accuracy of the ultimate prediction. If you implement visual control in your production processes, neural networks can boost the quality of products by superseding outdated algorithms. Besides this, they will optimize the EIoT solution. Conventional machine vision systems are pricey as they require the highest resolution cameras to catch minor defects in a product. They come with complex specific software that fails to respond to immediate changes.

Neural networks within machine vision systems can:

• Diminish camera requirements
• Self-learn on your data
• Automate high-speed operations

Indeed, industrial cameras use large-format global shutter sensors having high sensitivity and resolution to develop the highest quality images. Nevertheless, a well-trained ANN starts to identify images with time. It allows them to reduce the technical needs for the camera and ultimately cuts the final cost of the enterprise IoT implementation. You cannot compromise the quality of images to detect small components like parts in circuit boards; however, it is manageable for printing production, completeness checking, or food packaging.

After training, neural networks use massive amounts of data to identify objects from the images. It enables you to customize the EIoT solution and train the ANN to operate specifically with your product by processing your images.

For example, convolutional neural networks are utilized actively in the healthcare industry to detect X-rays and CT scans. The outcome offered by such custom systems is more precise than conventional ones. The capability to process information at high speeds permits the automation of production processes. When the problem or defect is caught, neural networks promptly report it to the operator or launch an intelligent reaction, like automating sorting. Hence, it allows real-time detection and rejection of defective production.

An exclusive example of how ANN is utilized for edge and fog computing. As per PSA, a neural network executed in a machine vision system permits lowering the number of defects by 90% in half a year, whereas production costs are decreased by 30%. Prospective areas for ANN in IoT visual control are quality assurance, sorting, production, collecting, marking, traffic control, and ADAS.

Big data advanced analytics for enterprise IoT:

Today, neural networks allow businesses to grab advantages like predictive maintenance, new revenue flows, asset management, etc. It is possible via deep neural networks (DNN) and the deep Learning (DL) method involving multiple layers for data processing. They detect hidden data trends and valuable information from a significant dataset by employing classification, clustering, and regression. It results in effective business solutions and the facilitation of business applications.

In comparison to traditional models, DL manages with the attributes that are expected for IoT data:

1. Assess the time of taking measurements
2. Resist the high noise of the enterprise IoT data
3. Conduct accurate real-time analysis
4. Determine heterogeneous and discordant data
5. Process a large amount of data

In practice, this implies that you don't require middle solutions to deliver and sort the data in the cloud or to analyze them in real-time. For example, full-cycle metallurgical enterprises can execute one solution to analyze the variable and unstructured data from metal mining, smelting, and final manufacturing products. Airplanes generate about 800TB of data per hour, making it impossible to process it all ideally using conventional analytical systems.

Today, DNN models are successful in the following enterprise IoT applications. 

Healthcare:

Today, it has become easy to predict disease using AI-based IoT systems, and this technology is developing for further improvements. For instance, the latest invention based on the neural network can detect the risk of heart attacks by up to 94.8%. DNN is also helpful in disease detection: the spectrogram of a person's voice received using IoT devices can identify voice pathologies after DNN processing. In general, ANN-based IoT health monitoring systems' accuracy is estimated to be above 85%.

Power consumption:

DL systems in the enterprise Internet of Things have provided results in power demand prediction based on power price forecasting, consumption data, anomaly, power theft detection, and leak detection. Smart meter data analysis permits you to calculate consumption, determine the unusual usage of electricity, and predict with an accuracy of more than 95%, which will help you to adjust energy consumption.

Manufacturing:

Neural networks help to use the most demanded IoT service among manufacturers properly- predictive equipment maintenance. It was ascertained to be a workable practice for mechanical and electrical systems. This network provides accurate real-time status monitoring and predicts proper life rest. Another best example is the recognition of employee activity by taking readings and following in-depth analysis.

Transportation & Logistics:

Deep Learning has made smart transportation systems possible. It offers better traffic congestion management by processing travel time, speed, weather, and occupational parking forecasting. Analytical reports based on vehicle data help to discover dangerous driving and possible issues before the failure happens.

As we know, the previous industries generate heterogeneous data. Therefore, the potential of ANN analytics within EIoT will be unlocked for multiple complicated systems.

When to consider ANN for enterprise IoT:

Till now, research in the field of ANNs been very active, and we cannot foretell all the advantages or pitfalls these solutions will convey. No doubt, neural networks find out correlations, models, and trends better than other algorithms. The IoT ecosystem's data will become more extensive, complex, and diverse with time. So, the development of neural networks is the future of IoT.

For now, we can look into the following features of neural networks for enterprise IoT:

• They suit the IoT ecosystem architecture, substituting alternative solutions with significant advantages.
• Essential for industrial image processing.
• Progressive ANN-based data analytics gets the high-level business value of the enterprise IoT solutions – improves productivity, and exactness, boosts sales, and produces informed business decisions.
• Training the ANN requires time and expenditure but will become fully customizable.
• We cannot conclude it is an affordable solution, but the advantages are priceless if the IoT ecosystem is executed accurately.

Therefore, if you are provided with a neural network as one of the opportunities for executing your idea within the IoT ecosystem, give it a chance. You never know, this solution will become a must-have in the coming years.

Technologies like blockchain, IoT, AR, VR, and AI are playing a big role in transforming the gambling industry. They are changing the way of gambling and players all around the world are liking this innovative approach. 

The Internet of things has added a lot of attraction to casinos because with the help of IoT, offering gambling according to the regulation, to ensure players' safety, secure their assets, data security, and excellent player gaming experience becomes so much easier. Not only the gambling industry but also other various industries have adopted it and collaborating with AI, Crypto, and blockchain gives a new shape to the casino world. According to the study, it is expected more than 41 billion IoT devices will be used by 2027. All digital devices such as smartphones, PCs, digital watches, cameras, and other smart gadgets are examples of IoT.

In this article, we are going to discuss how blockchain and IoT are bringing fruitful results in the gambling industry. And why the demand for blockchain development services is so high in the market.

IoT Basics:

IoT is a network of physical objects that are connected with each other by sensors, software, and other technologies to connect and exchange data in a secure and smooth way over the Internet. IoT is defining the gaming industry with positive and fruitful way. 

Before diving in-depth, let’s know about blockchain and IoT.

Blockchain Basics

The main objective of blockchain is to record data in the form of blocks and all blocks are linked together in a chain. That means blockchain is an immutable ledger where all records are saved but cannot be changed, deleted, or destroyed. 

Basically, it is an advanced database mechanism that offers you high security and transparency. There are four types of blockchains:

• Public blockchain
• Private blockchain
• Hybrid blockchain
• Consortium Blockchain

Lets’ know the positive aspects of Blockchain and IoT in gambling business Industry.

Benefits of Blockchain in Gambling Industry

Here are the reasons for the popularity of blockchain and IoT in gambling world and most games and service providers and online casinos are using both technologies in order to create a difference. 

• High Security
  

Blockchain offers you high-end security and when you make any transaction using cryptocurrencies then it will automatically be added to the distributed ledger and will automatically be added in the whole blocks and entry of new coins is added in the blockchain. 

Blockchain in the casino is offering high security to both players and owners. With its help, there is no need to do registration at casinos and there is no need to validate yourself, and no credit card information is required there. You can do all without sharing your personal data and no one regulates you due to the absence of central authorities.

• Anonymity
  

As we all know that according to a specific location, there are certain rules to regulate online casino business and as a user, you have to follow these rules. But with the help of blockchain, you can enjoy any casino all over the world and you can make payments without facing any issues and no one will know your identity. Cryptocurrency and blockchain are not regulated by any central authority and you can earn huge profits by accessing all casinos all over the world and crypto can be used for payment. 

At present, privacy is everything and you can gamble and make transactions without being noticed by anyone because no one can track you here and you have no need to share your personal information.

• Instant and Cost-effective

Blockchain makes it possible to do fast and instant transactions. As we all know that crypto is based on blockchain and not regulated by a central authority so it means there are no mediators and you can make your transaction in a faster way. And cost-effectiveness is another reason that is making it more popular and it charges less than credit cards, debit cards and traditional platforms. 

• Transparency, Efficiency, and Access
  

When you integrate blockchain in the online gambling industry, then you get transparency and no one can make fraud with you. Like you cannot trust traditional casinos, and online platforms for reliable betting services but on blockchain oriented casinos you can. Because here blockchain maintains all records that are impossible to manipulate. 

You can also enjoy casino games without registration because it uses only your wallet address so it becomes quite easy to access and platform efficiency also improves. 

• Smart chips
  

In online casinos, there is a huge amount of data and managing that is quite a tedious task and thanks to IoT that has made it quite easy and user-friendly. With the help of RFID microchips, all illegal activities have become so minimal. RFID microprocessors have made it possible to take care of all aspects of online casinos.

So, we can say that IoT has increased the security of casinos and now players can enjoy gambling services in an easy way. 

Final Word

This article helps you to know all about the IoT and Blockchain and how they are bringing positive changes in the online casino world and gambling industry. After reading this article, we can say that now players and bettors can enjoy online gambling in an effective way without facing any issues. Now they are paying full attention to gambling without caring about extra issues. You can also invest in the gambling business with the help of a sports betting developmet company.

With the advent of the Internet of Things, Big Data is becoming more and more important. After all, when you have devices that are constantly collecting data, you need somewhere to store it all. But the Internet of Things is not just changing the way we store data; it’s changing the way we collect and use it as well. In this blog post, we will explore how the Internet of Things is transforming Big Data. From new data sources to new ways of analyzing data, the Internet of Things is changing the Big Data landscape in a big way.

How is the Internet of Things transforming Big Data?

The Internet of Things is transforming Big Data in a number of ways. One way is by making it possible to collect more data than ever before. This is because devices that are connected to the Internet can generate a huge amount of data. This data can be used to help businesses and organizations make better decisions.

Another way the Internet of Things is transforming Big Data is by making it easier to process and analyze this data. This is because there are now many tools and technologies that can help with this. One example is machine learning, which can be used to find patterns in data.

The Internet of Things is also changing the way we think about Big Data. This is because it’s not just about collecting large amounts of data – it’s also about understanding how this data can be used to improve our lives and businesses.

The Benefits of the Internet of Things for Big Data

1. The internet of things offers a number of benefits for big data.
2. It allows for a greater volume of data to be collected and stored.
3. Also, it provides a more diverse range of data types, which can be used to create more accurate and comprehensive models.
4. It enables real-time data collection and analysis, which can help organizations make better decisions and take action more quickly.
5. It can improve the accuracy of predictions by using historical data to train predictive models.
6. Finally, the internet of things can help reduce the cost of storing and processing big data.

The Challenges of the Internet of Things for Big Data

The internet of things is transforming big data in a number of ways. One challenge is the sheer volume of data that is generated by devices and sensors. Another challenge is the variety of data formats, which can make it difficult to derive insights. Additionally, the real-time nature of data from the internet of things presents challenges for traditional big data infrastructure.

Conclusion

The Internet of Things is bringing a new level of connectivity to the world, and with it, a huge influx of data. This data is transforming how businesses operate, giving them new insights into their customers and operations.

The Internet of Things is also changing how we interact with the world around us, making our lives more convenient and efficient. With so much potential, it's no wonder that the Internet of Things is one of the most talked-about topics in the tech world today.

IoT is disrupting almost every industry sector including communications. As power consumption has become a challenge for IoT devices, cellular IoT has introduced some standards that are cutting-edge. Let’s take a look at those standards and their device categories.

Remember the days when the “E” icon on the notification bar of our phones used to make us excited? 

Well, if we compare that to today, technology has skyrocketed like anything. It was just a matter of time before that E icon turned to 4G LTE.

Today, there are billions of devices that run on the 4G network providing lightning-fast internet to the users. And it does not end here. The wave of 5G is ready to take on the world. Though some countries have already deployed 5G, it is yet to conquer the entire world.

Now, IoT is not a buzzword anymore. It is an awesome technology that connects various internet-enabled devices and is known to everybody. The use of IoT allows devices to share data at a faster pace. But, there is one challenge!

As these devices are connected to cellular networks like 3G and 4G LTE, they consume a lot of power. In a way, it is acceptable, but not if the devices are sending a small amount of data occasionally. So what’s the solution here? Cellular IoT!

Cellular IoT deals with some of the best IoT standards and devices that make the existing cellular technology fit for low-powered devices. If you are interested to know how; read ahead and find out!

Why are IoT LTE devices necessary?

Well, the need for IoT devices comes into the picture when we analyze applications like predictive maintenance, asset tracking, fleet management, inventory management, remote service, etc.

All these applications are backed by powerful yet sensitive devices that transmit data to ensure that all your business processes are running fine. LTE is the technology that helps them. IoT devices under LTE can be classified based on the LTE standards!

LTE-M/ Cat-M1:

This standard covers devices that run under the bandwidth of 1.4 MHz. Most of the devices under the standard are smart meters, fleet management devices, and asset tracking devices.

Cat-1:

The operating bandwidth of Cat-1 devices is 20 MHz which allows for devices like ATMs, POS terminals, and wearables to operate.

Cat-4:

The devices under Cat-4 have the maximum download and upload speed, which makes them ideal for applications like autonomous vehicles, real-time video, and in-car infotainment.

NB-IoT/ Cat-NB1:

The IoT LTE devices under NB-IoT have the maximum latency, which makes them crucial for applications like parking sensors, street lighting, industrial monitors, and more.

What are the various IoT LTE devices categories?

Well, if we talk about the device categories, IoT LTE devices can be classified into four categories based on cellular IoT standards. The newest of these four standards are LTE-M and NB-IoT.

Let’s read ahead and find out about the IoT LTE device categories!

1. LTE-M/ Cat-M1

Let’s begin with the LTE-M standard. The LTE-M standard is an excellent discovery that is ideal for devices that require less power and less bandwidth. Here are some key pointers related to the device categories of LTE-M!

• The devices based on the LTE-M standard have an upload speed of 1 Mbps, and the same is the download speed.
• On top of that, the latency in the case of LTE-M devices is 10-15 milliseconds. The latency is enough to ensure that the required data is transmitted at regular intervals.
• The bandwidth of the LTE-M is enough to ensure that the devices are able to function well in the prevailing 2G and 3G applications.
• The best thing about the LTE-M standard is handoff for devices. It allows seamless handoff that makes the standard ideal for applications like asset tracking and fleet management where devices are on the move.
• Cat-M1 was created as an integral part of Release 13 of the 3GPP’s LTE standards.

2. Cat-1

Apart from the above-described device categories, Cat-1 is a category that is a part of Release 8 of the 3GPP standard. Though it is a part of the old technology, it is still widely used across the globe. Here are some features of the Cat-1!

• The Cat-1 standard is made for IoT device categories that have low and medium bandwidth needs.
• The speed of the Cat-1 device is more than that of LTE-M. The upload speed of the Cat-1 devices is 5 Mbps, and the download speed is 10 Mbps.
• One of the best things about Cat-1 is that it has less latency. The latency of the signals is just 50-100 milliseconds.
• The Cat-1 standard uses a massive bandwidth of 20 Mhz in a full duplex. The full duplex capability of the devices allows for smooth handoff, making it ideal for wearables, ATMs, POS terminals, etc.

3. Cat-4

Well, the Cat-4 standard is what it takes to support applications like autonomous cars. The speed of devices in this standard is way more than Cat-1. It can provide you with 50 Mbps upload speed, and 150 Mbps download speed.

The best advantage of the Cat-4 standard is that it supports in-car infotainment, in-car hotspots, and video surveillance.

4. NB-IoT/ Cat-NB1

After the LTE-M, there is NB-IoT or Cat-NB1 standard. Just like LTE-M, there are many aspects that make it a bit different and unique. Here are some key pointers about the devices supporting the NB1 standard.

• The low-cost technology makes use of DSSS modulation technology vs. LTE spread technology to ensure connectivity.
• The cost factor of the technology is not the only USP. The devices that come under Cat-NB1 have less power consumption, offer excellent in-building coverage, and have longer battery life.
• If we talk about the upload and download speed of the NB-IoT device category, it is relatively less compared to LTE-M. The upload speed is 66 kbps, and the download speed is 26 kbps. This is in half duplex mode.
• The latency of NB-IoT is also more than the LTE-M. It oscillates between 1.6 to 10 seconds. Though it seems way more, there are advantages to it. The latency is ideal for small, intermittent data transmissions.
• NB-IoT is also part of Release 13 of the 3GPP’s LTE standard. It is an LPWAN technology that works on a licensed spectrum.
• The devices that come under this standard are smart gas, street lights, parking sensors, etc.

Other than these device and standard categories, there are two more standards:

5. Cat-0

As there is a need for low-cost devices and processes, Cat-0 lays the groundwork for that. It eliminates the need for features that require a high data rate in Cat-1. On top of all, Cat-0 is slowly doing the groundwork for Cat-M by replacing 2G.

6. EC-GSM

It is a standard that does not have as much buzz as the LTE-M and NB-IoT. But, it has been tested by brands like Ericsson and Intel for supreme practicality and modularity.

Why Do We Need To Care?

Well, if you are a cellular carrier service provider, you have to care about it. There are many factors that need to be considered while choosing the IoT LTE device category. Here is a brief elaboration of some of the critical ones!

1. Power consumption:

Out of all the IoT LTE devices listed above, those who come under the Cat-4 consume the maximum power. After that come the devices under Cat-1. Cat-M1 and NB-IoT devices are the ones that have the minimum power consumption.

2. Battery life:

Battery life is the key factor if the devices are placed in remote locations like the agricultural field. If you are choosing LTE IoT devices, go for devices under standards Cat-M1 and NB-IoT.

3. Cost:

If cost is your concern, then again, Cat-M1 and NB-IoT are the ideal picks for you. They are best for high-volume device applications. Devices under Cat-1 and Cat-4 are more pricey.

4. Adoption:

When it comes to adoption, the adoption of LTE-M and NB-IoT are quickly being adopted by carrier service providers across the globe.

5. Latency:

Latency is the highest in NB-IoT, which makes it ideal for applications that do not need to send continuous data. LTE-M is a bit faster than NB-IoT. Cat-4 is the fastest, which makes it ideal for video applications.

Conclusion

So, now we are clear about what type of IoT devices are under each standard of LTE. LTE-M and NB-IoT are the standards that are being quickly adopted as they are low cost, consume less power, and have max battery life. To make an informed choice, it is necessary for you to analyze each aspect closely. As of now, carrier companies are inclined toward adopting  NB-IoT and LTE-M as they can serve vast applications while being balanced in all aspects.

The Internet of Things is changing the way we consume and interact with things in our everyday lives. IoT gives objects digital identity. This means that they can be monitored, controlled, and synced with other devices wirelessly. The article looks at how the IoT will affect the electric vehicle industry in the future.

Let's begin!

Table of contents

• How will the IoT affect the Electric Vehicle Industry?
• What are the Advantages and Disadvantages of the IoT in the EV industry?
• What Industries Have Benefited from the IoT?
• Final Thought

How will the IoT affect the Electric Vehicle Industry?

The IoT has the potential to change the way we interact with the world around us, and it is already having an impact on the electric vehicle (EV) industry.

One way that the IoT is affecting EVs is by making it possible for cars to communicate with each other and with infrastructures, such as traffic lights and parking spaces. This communication can make driving more efficient and safer. For example, if two connected cars are approaching an intersection at the same time, they can communicate with each other to decide who has the right of way. This eliminates the need for one car to stop and wait for the other to pass.

Another way that the IoT is impacting EVs is by providing data that can be used to improve the efficiency of charging stations. Connected chargers can communicate with each other and with EV batteries to optimize charging times and reduce congestion at charging stations. This data can also be used to help plan future charging infrastructure.

The IoT also has the potential to change how we think about ownership of EVs. In a traditional ownership model, a person buys a car and then pays for its maintenance, fuel, and insurance. With an IoT-enabled EV, it would be possible for someone else to own the vehicle and provide these services as part of a subscription service. This could make EVs more affordable.

What are the Advantages and Disadvantages of the IoT in the EV industry?

As the electric vehicle industry continues to grow, so too does the role of the IoT. The advantages of the IoT in the EV industry include increased efficiency and accuracy in data collection, improved safety and security, and enhanced customer experience. Meanwhile, some of the disadvantages of the IoT in the EV industry include potential privacy concerns and data breaches, as well as the need for a reliable and secure network infrastructure.

The Advantages of the IoT in the EV industry

• It makes it easier for you to control your car's climate and other functions remotely while you're not in it.
• You can use an app on your phone or laptop to control things like lights, power windows, etc., even if they're not connected directly to your vehicle's system (like a garage door opener). You could also use this tech for home automation systems like Nest or Harmony which allow you to control all kinds of things from anywhere in your house.
• You can share information about where you parked your car with friends who might need help finding it later on or help them find it.

The Disadvantages of the IoT in the EV industry

The IoT is a great way to increase your EV industry's efficiency and success, but it can also be difficult to implement. Here are some disadvantages of using the IoT in the EV industry:

• The cost of implementation is high. This may be because there are many different types of devices that need to be connected, and each requires different types of software and hardware.
• The amount of data that needs to be collected can be overwhelming for some businesses, especially if they don't have experience with big data collection or storage systems.
• There are many different types of devices that need to be connected some may not work together well or may require additional programming. So it can take time and money before you're able to see any benefits from your investment in the IoT system.

What Industries Have Benefited from the IoT?

The Internet of Things (IoT) has had a significant impact on the automobile sector. One of the most major developments has been in the manufacturing of cars. The introduction of sensors and other linked devices has enabled manufacturers to collect data on how cars are used, leading to changes in the production process. As a result, automobiles are of higher quality and more efficient.

Another area where IoT technology is making a difference in car safety is. Automakers can discover possible safety hazards and solve them by gathering data from sensors and other linked systems. As a result, automobiles are safer and there are fewer accidents.

Finally, IoT technology is transforming how customers engage with their automobiles. Customers are increasingly utilizing their cell phones and other linked devices to manage their automobiles.

Everything from starting the engine to opening the doors and controlling the temperature control is covered. As this trend continues, it is probable that even more capabilities that allow consumers to operate their automobiles in novel ways will be added.

Final Thought

The IoT will play a major role in the electric vehicle industry by providing real-time data that can be used to improve the efficiency of production and distribution. In addition, the IoT can also be used to monitor the performance of electric vehicles and provide feedback to drivers in order to help them optimize their routes and usage. Ultimately, the goal is to make electric vehicles more efficient, reliable, and affordable for everyone.

What is so unique about IoT technology? With IoT, there is neither a need for human-to-computer nor human-to-human interaction. In other words, everything is connected yet independent. 

If we bring Salesforce to the picture, we have an intelligent solution, i.e., Salesforce IoT Cloud, that can get all your data in a single place. Sounds interesting, right? So, what is Salesforce IoT cloud, and how does it benefit businesses? It makes sense to partner with a reliable Salesforce consultant to know more about this robust solution. 

What is Salesforce IoT cloud?

Salesforce IoT Cloud allows organizations to create and enrich customer profiles and enter data irrespective of location, channel, time, or device. The robust solution helps implement interaction IoT laws, personalizes outcomes, or allows for simple integration with the Salesforce mobile app. The platform supports organizations to handle enormous volumes of data gathered from different processes, network devices, and locations.

Its practical approach helps develop excellent customer relationships, improving client retention and engagement. By assisting organizations to monetize their IoT investment, Salesforce IoT cloud allows organizations to provide a competitive edge over any connected device. The Salesforce IoT Cloud platform can be integrated with other Salesforce services such as Salesforce sales cloud, service cloud, community cloud, and marketing cloud.

Top Benefits of Salesforce IoT cloud?

Data Analysis with Einstein Analytics: Salesforce IoT cloud utilizes the Einstein Analytics platform to process data gathered from different sources and analyze it. This helps users better understand consumer behavior and preferences while undertaking the necessary steps to attract and retain them.

Augments Customer Experience: All the historical data regarding customer interaction gets stored on the Salesforce IoT cloud platform, which considers their location, service background, and more to provide organizations with a complete view of customer behavior. In the long run, organizations will become more proactive by anticipating customer demands, thereby providing a superior customer experience.

Low or No Code Approach: Due to its low code approach, the Salesforce IoT Cloud allows business executives to carry out their IoT processes without bothering the IT department. The orchestration rules can be set up in a way like that of a Salesforce marketing cloud feature, i.e., 'customer journey.' IoT will automate your business operations by placing triggers and responses in place.

Customer Context: This feature entails the machine learning aspect of Salesforce IoT cloud records and analyses past actions and behaviors of customers to make real-time decisions. The feature considers Customer History, location, and Service History and pools it with IoT device data to provide you with a complete picture of what's occurring.

More Visibility: The process involved in implementing a Salesforce IoT system is a primary consideration in choosing it. Businesses, too, could get a bird's eye view of the process in progress from the traffic view, which is a visual representation of an organization's ROI in different aspects. The visual panel allows organizations to see how IoT products perform in a constantly evolving consumer landscape.  

Increases Client Referrals: Clients expect hassle-free connectivity with businesses. Implementing the Salesforce IoT cloud platform makes it possible to build strong customer relationships by being accessible to them all the while.

Enhances R&D Activities: Businesses can make necessary changes to suit customer needs and requirements by tracking consumer behavior and preferences. Besides this, it is also possible to predict the taste of future customers from a pre-emptive perspective. Businesses can make quick decisions or fix the problems by getting a brief understanding of what's operative and what isn't. This improves service delivery.

Increases Lead Generation Process: Besides B2B transactions, the Salesforce IoT cloud can help the sales department gain information about the products linked with the Salesforce IoT cloud. With this information, the Sales team will be able to identify expired items, whose warranty expiration is approaching, and more. They can leverage this data to upgrade their sales processes and reach targeted customers. Businesses can create personalized deals or pitch a new product to the customers if their existing product isn't working well. Most of the data gathered can be used to forecast customer needs in several ways.

Provide Complete Perspective of Customers: By leveraging the personalized reports, Salesforce IoT provides businesses with a 360-degree view of their customers. Based on an organization's requirements, it is possible to modify the advantages.

Seamless Integration with Other Systems: Besides empowering organizations to provide services independently by gathering and processing data, Salesforce IoT cloud is capable of expanding its functionality, permitting third-party integration. Consequently, businesses get to access data from multiple sources, enabling them to explore other aspects of a business.

Final Words:

The Salesforce IoT cloud provides a complete and exact picture of how customers utilize the goods and services by integrating data gathered by their apps, irrespective of their position. The data collected can be leveraged by businesses to create personalized sales and marketing strategies while influencing customer opinion. So, implementing Salesforce IoT cloud will take the client management of every company to a new level. The innovative cloud solution offers infinite potential, which businesses can leverage to make informed business decisions. So, companies now need to integrate the Salesforce IoT cloud into their operations. However, if you wish to integrate the Salesforce IoT cloud within your business ecosystem, ensure you get in touch with a certified Salesforce Consulting Partner. 

Against the backdrop of digital technology and the industrial revolution, the Internet of Things has become the most influential and disruptive of all the latest technologies. As an advanced technology, IoT is showing a palpable difference in how businesses operate. 

Although the Fourth Industrial Revolution is still in its infancy, early adopters of this advanced technology are edging out the competition with their competitive advantage. 

Businesses eager to become a part of this disruptive technology are jostling against each other to implement IoT solutions. Yet, they are unaware of the steps in effective implementation and the challenges they might face during the process. 

This is a complete guide– the only one you’ll need – that focuses on delivering effective and uncomplicated IoT implementation. 

Key Elements of IoT

There are three main elements of IoT technology:

• Connectivity:

IoT devices are connected to the internet and have a URI – Unique Resource Identifier – that can relay data to the connected network. The devices can be connected among themselves to a centralized server, a cloud, or a network of servers.

• Data Communication:

IoT devices continuously share data with other devices in the network or the server. 

• Interaction

IoT devices do not simply gather data. They transmit it to their endpoints or server. There is no point in collecting data if it is not put to good use. The collected data is used to deliver IoT smart solutions in automation, take real-time business decisions, formulate strategies, or monitor processes. 

How Does IoT work?

IoT devices have URI and come with embedded sensors. With these sensors, the devices sense their environment and gather information. For example, the devices could be air conditioners, smart watches, cars, etc. Then, all the devices dump their collected data into the IoT platform or gateway. 

The IoT platform then performs analytics on the data from various sources and derives useful information per the requirement. 

What are the Layers in IoT Architecture?

Although there isn’t a standard IoT structure that’s universally accepted, the 4-layer architecture is considered to be the basic form. The four layers include perception, network, middleware, and application.

• Perception:

Perception is the first or the physical layer of IoT architecture. All the sensors, edge devices, and actuators gather useful information based on the project needs in this layer. The purpose of this layer is to gather data and transfer it to the next layer. 

• Network:

It is the connecting layer between perception and application. This layer gathers information from the perception and transmits the data to other devices or servers. 

• Middleware: 

The middleware layer offers storage and processing capabilities. It stores the incoming data and applies appropriate analytics based on requirements. 

• Application: 

The user interacts with the application layer, responsible for taking specific services to the end-user. 

Implementation Requirements

Effective and seamless implementation of IoT depends on specific tools, such as:

• High-Level Security 

Security is one of the fundamental IoT implementation requirements. Since the IoT devices gather real-time sensitive data about the environment, it is critical to put in place high-level security measures that ensure that sensitive information stays protected and confidential.  

• Asset Management

Asset management includes the software, hardware, and processes that ensure that the devices are registered, upgraded, secured, and well-managed. 

• Cloud Computing

Since massive amounts of structured and unstructured data are gathered and processed, it is stored in the cloud. The cloud acts as a centralized repository of resources that allows the data to be accessed easily. Cloud computing ensures seamless communication between various IoT devices. 

• Data Analytics

With advanced algorithms, large amounts of data are processed and analyzed from the cloud platform. As a result, you can derive trends based on the analytics, and corrective action can be taken. 

What are the IoT Implementation Steps?

Knowing the appropriate IoT implementation steps will help your business align your goals and expectations against the solution. You can also ensure the entire process is time-bound, cost-efficient, and satisfies all your business needs. 

Set Business Objectives 

IoT implementation should serve your business goals and objectives. Unfortunately, not every entrepreneur is an accomplished technician or computer-savvy. You can hire experts if you lack the practical know-how regarding IoT, the components needed, and specialist knowledge. 

Think of what you will accomplish with IoT, such as improving customer experience, eliminating operational inconsistencies, reducing costs, etc. With a clear understanding of IoT technology, you should be able to align your business needs to IoT applications. 

Hardware Components and Tools

Selecting the necessary tools, components, hardware, and software systems needed for the implementation is the next critical step. First, you must choose the tools and technology, keeping in mind connectivity and interoperability. 

You should also select the right IoT platform that acts as a centralized repository for collecting and controlling all aspects of the network and devices. You can choose to have a custom-made platform or get one from suppliers. 

Some of the major components you require for implementation include,

• Sensors
• Gateways
• Communication protocols
• IoT platforms
• Analytics and data management software

Implementation

Before initiating the implementation process, it is recommended that you put together a team of IoT experts and professionals with selected use case experience and knowledge. Make sure that the team comprises experts from operations and IT with a specific skill set in IoT. 

A typical team should be experts with skills in mechanical engineering, embedded system design, electrical and industrial design, technical expertise, and front/back-end development. 

Prototyping

Before giving the go-ahead, the team must develop an Internet of Things implementation prototype. 

A prototype will help you experiment and identify fault lines, connectivity, and compatibility issues. After testing the prototype, you can include modified design ideas. 

Integrate with Advanced technologies

After the sensors gather useful data, you can add layers of other technologies such as analytics, edge computing, and machine learning. 

The amount of unstructured data collected by the sensors far exceeds structured data. However, both structured and unstructured, machine learning, deep learning neural systems, and cognitive computing technologies can be used for improvement. 

Take Security Measures

Security is one of the top concerns of most businesses. With IoT depending predominantly on the internet for functioning, it is prone to security attacks. However, communication protocols, endpoint security, encryption, and access control management can minimize security breaches. 

Although there are no standardized IoT implementation steps, most projects follow these processes. But the exact sequence of IoT implementation depends on your project’s specific needs.

Challenges in IoT Implementation

Every new technology comes with its own set of implementation challenges. 

When you keep these challenges of IoT implementation in mind, you’ll be better equipped to handle them. 

• Lack of Network Security

When your entire system is dependent on the network connectivity for functioning, you are just adding another layer of security concern to deal with. 

Unless you have a robust network security system, you are bound to face issues such as hacking into the servers or devices. Unfortunately, the IoT hacking statistics are rising, with over 1.5 million security breaches reported in 2021 alone. 

• Data Retention and Storage 

IoT devices continually gather data, and over time the data becomes unwieldy to handle. Such massive amounts of data need high-capacity storage units and advanced IoT analytics technologies. 

• Lack of Compatibility 

IoT implementation involves several sensors, devices, and tools, and a successful implementation largely depends on the seamless integration between these systems. In addition, since there are no standards for devices or protocols, there could be major compatibility issues during implementation. 

IoT is the latest technology that is delivering promising results. Yet, similar to any technology, without proper implementation, your businesses can’t hope to leverage its immense benefits. 

Taking chances with IoT implementation is not a smart business move, as your productivity, security, customer experience, and future depend on proper and effective implementation. The only way to harness this technology would be to seek a reliable IoT app development company that can take your initiatives towards success.

The Internet of Things network of interconnected devices such as sensors, gateways, and computers that transfer the data over a wireless network eliminates the need for human intervention. IoT devices can be remotely tracked, and controlled in real-time. It also enables users to connect and interact with others over the internet. The applications of IoT are tremendous and it can be found in every part of human life, ranging from smartwatches to self-driving cars.

What Is IoT Device Management?

IoT device management refers to the ability to remotely accessing, monitoring, tracking and managing the functionality of IoT devices in order to ensure the deployed devices are secure, up to date and compliant. Here’s a breakdown of the reasons why businesses need an IoT device management platform:

• Accelerate time to market

One of the biggest perks of the IoT device management platform is that it helps developers to reduce the time frame of product development and testing, thereby enabling them to release products to market on time. Furthermore, streamlining and automating network and device management tasks enables businesses to concentrate on their core competencies while lowering costs.

• Secure device on and off boarding

A smart device is not, and should not be, automatically connected to an IoT network. A secure approach is required to configure and add only authorized devices to the network architecture, and a network and device management tool makes this simple and straightforward. End nodes can be authenticated and secure communications established via a web interface by registering and attaching them to the authorized base station using their network keys and identification credentials. Only after the node has completed the onboarding process it will be allowed to join the network and securely transmit data using network-level encryption. Similarly, if deployed nodes are no longer required, they can be easily offboarded from the web UI – without having to travel to the field.

• Streamline network monitoring and troubleshooting

IoT device management platform enables firms to gain a top to bottom view of all registered nodes, network traffic and their status in a single interface. It acts as a central hub for data aggregation across base stations in a network with multiple base stations. This is especially useful for monitoring and identifying unexpected network and device problems. Businesses can quickly identify and determine the root causes of bottlenecks with real-time visibility into incoming data, battery level, and keep-alive messages from individual nodes. For example, if a node fails to deliver messages on a regular basis, the radio traffic may be overloaded. If, on the other hand, it completely disconnects from the network and stops sending messages, it could be due to a hardware or firmware flaw. Similarly, by continuously monitoring battery levels, firms can schedule maintenance for multiple devices at the same time, saving time and money.

• Simplifies downstream application deployment

IoT device management platform serves as a link between the edge network, downstream data servers of users and enterprise applications. Using protocols like MQTT and API calls, a versatile IoT device management solution allows for easy integration with any backend system, whether on-premises or in the cloud. As a result, firms can easily deploy and scale IoT applications to meet changing business needs, whether by adding new devices to an existing app or connecting to a new analytics platform. It also enables businesses to gain a better view of all current integrations and applications from a single window thereby simplifying the management of an entire IoT project.

• Eliminate security risks

Considering the ever-increasing complexity of cyber-attacks, it is critical to equip connected IoT network components such as base stations and routers with the most up-to-date security features. A manual approach cannot keep up with the demand for continuous and timely updates to these critical network infrastructures, particularly those deployed remotely - Here comes the need for an IoT device management tool. It will enable businesses to update operating systems automatically and run security updates from afar, helping them to save money while also ensuring their remote base stations are well-prepared against malicious attacks. Furthermore, round-the-clock monitoring of the network assists firms in the early detection of unusual patterns, such as an increase in data traffic, which could indicate a breach and eliminate security hazards.

Conclusion

The advancements in IoT and AI services have made it critical for businesses to rely on efficient and secure methods to manage and control their networks and devices at scale. An IoT device management platform helps businesses to track, manage and gain real-time insights into all devices and stay on top of their deployment. When combined with a robust wireless solution, it enables firms to seamlessly expand their IoT network and solutions at minimal cost and complexity.

How Doews IoT help in Retail? Continuous and seamless communication is now a reality between people, processes and things.  IoT has been enabling retailers to connect with people and businesses and gain useful insight about product performance and engagement of people with such products. 

Importance of IoT in Retail

• It helps improve customer experience in new ways and helps brick and mortar shops compete with their online counterparts by engaging customers in different ways.
• IoT can track customer preferences, analyze their habits and share relevant information with the marketing teams and help improve the product or brand features and design and keep the customer updated on new products, delivery status etc.
• Using IoT retailers can increase efficiency and profitability in various ways for their benefit.
• IoT can significantly improve the overall customer experience, like automated checkouts and integration with messaging platforms and order systems.
• It helps increase efficiency in transportation and logistics by reducing the time to deliver goods to market or store. It helps in vehicle management, and tracking deliveries. This helps in reducing costs, improving the bottom line and increasing customer satisfaction.
• Inventory management becomes easier with IoT. Tracking inventory is much easier and simpler from the stocking of goods to initiating a purchase.
• It helps increase operational efficiency in warehouses, by optimizing temperature controls, improving maintenance, and managing the warehouse. 

Use Cases of IoT in Retail

1. IoT is used in Facility management to ensure day-to-day areas are clean and can be used to monitor consumable supplies levels. It can be used to monitor store environments like temperature, lighting, ventilation and refrigeration. IoT can identify key areas that can provide a complete 360 degrees view of facility management.
2. It can help in tracking the number of persons entering a facility. This is especially useful because of the pandemic situation, to ensure that no overcrowding takes place.
   Occupancy sensors provide vital data on store traffic patterns and also on the time spent in any particular area. This helps retailers with better planning and product placement strategies. This helps in guided selling with more effective display setups, layouts, and space management.
3. IoT helps in a big way for Supply chain and logistics, by providing information on the stock levels. 
4. IoT helps in asset tracking in items like shopping carts and baskets. Sensors can ensure that location data is available for all carts making retrieval easy. It can help lock carts if they are taken out of location.
5. IoT devices can and are being used to personalize user experience. Bluetooth beacons are used to send personalized real-time alerts to phones when the customer is near an aisle or a store. This can prompt a customer to enter the store or look at the aisle area and take advantage of offers etc. IoT-based beacons, helps Target, collect user data and also send hyper-personalized content to customers.
6. Smart shelves are another example of innovative IoT ideas. Maintaining shelves to refill products or ensure correct items are placed on the right shelves is a time-consuming task. Smart shelves automate these tasks easily. They can help save time and resolve manual errors.

Businesses should utilize new technologies to revolutionize the retail sector in a better way. Digitalization or digital transformation of brick and mortar stores is not a new concept. With every industry wanting to improve its services and facilities and trying to stay ahead of the competition, digitalization in retail industry is playing a big role in this transformation. To summarize, digitalization helps in enhanced data collection, helps data-driven customer insights, gives a better customer experience, and increases profits and productivity. It encourages a digital culture.

There have been various innovations that have caused a stir in the healthcare business. As we have Artificial Intelligence, Machine Learning, and Augmented Reality technologies. As a result, you see their applications in every field or business, however, some of them are just overhyped or gimmicks.

However, the Internet of Things (IoT) is the most thriving technology, and IoT in healthcare has brought in a plethora of applications that are more than simply gimmicks and are actually pretty beneficial. Aside from the healthcare industry, there is a high need for IoT developers in general. Businesses in a variety of industries, including healthcare, are investing heavily in IoT app development. Let's take a look at how IoT is progressing in the healthcare business.

The benefits of IoT in healthcare are:

1) Simultaneous Reporting and Monitoring

Real-time monitoring through linked devices has the potential to save a million lives in the case of a medical emergency such as heart failure, diabetes, asthma attacks, and so on. Connected devices can acquire relevant medical and health-related data by monitoring the state in real-time using a smart medical gadget connected to a smartphone app.

 The linked IoT gadget captures and transmits health data such as blood pressure, oxygen, and blood sugar levels, as well as weight and ECGs. The data is kept in the cloud and can be shared with an authorized individual according to the sharing access authorization.

 Furthermore, the mentioned individual may be a physician, an insurance company, a participating health firm, or an external consultant, and it will allow them to check into the situation.

2)  Data Assortment and Analysis

Managing a large volume of data is not as simple as it seems for healthcare practitioners. Data acquired in real-time by IoT-enabled mobile devices may be evaluated and separated using IoT-powered mobility solutions.

This will lower the amount of raw data collected while also enabling crucial healthcare analytics and data-driven insights, which will eventually reduce mistakes and speed up decision-making.

3.)Tracking and Alerts

In life-threatening situations, real-time tracking and alerts can be a lifesaver by protecting a crucial patient's health with continual notifications and real-time alerts for proper monitoring, analysis, and diagnosis. IoT-powered healthcare mobility solutions provide real-time tracking, alerting, and monitoring.

This allows for hands-on treatments, more precision, and appropriate intervention by doctors, thereby enhancing the overall patient care delivery results.

4.) Remote Medical Assistance

In the case of an emergency, users may use smart smartphone applications to call a doctor who is thousands of kilometers away. With mobility solutions in healthcare, doctors may check on patients and diagnose illnesses while they are on the road.

Furthermore, various IoT-based healthcare delivery chains are planning to construct machines that may administer medications based on a patient's prescription and ailment-related data available via connected devices. IoT will improve hospital patient care. As a result, people's healthcare costs will be reduced.

What are the challenges of IoT in healthcare?

1) Data Security and Privacy:

Data Security and Privacy are two of the most serious concerns that IoT faces. IoT-enabled mobile devices collect data in real-time, however, the majority of them do not follow data protocols and standards.

There is a great deal of uncertainty around data ownership and regulation. As a result, data held within IoT-enabled devices are vulnerable to data theft, making the data more vulnerable to hackers who can hack into the system and jeopardize sensitive health information.

Fraudulent health claims and the production of phony IDs for purchasing and selling pharmaceuticals are two instances of how IoT device data is being misused.

2) Data Overload and Accuracy:

It is difficult to total information for essential bits of knowledge and inquiry due to the inconsistency of information and correspondence protocols. IoT collects information in large quantities, and for proper information inquiry, the information should be isolated in parts without overburdening and with accurate accuracy for better results. Furthermore, overburdening of information may have an effect on the dynamic cycle in the accommodation area in the long term.

3) Cost

This point is probably not surprising to you. Costs are one of the most significant challenges when considering IoT application development for medical services flexible setups. In any event, the costs are well worth the effort if the IoT implementation addresses a genuine need.

While establishing an IoT application will cost you a lot of money and assets, the benefits will be significant when your company saves time and labor, all while further expanding the business processes, providing additional income streams, and opening up more business opportunities through IoT.

Applications of IoT in healthcare

The growth of IoT is fascinating for everyone because of its diverse range of applications in numerous industries. It has numerous applications in healthcare. Here are some notable Internet of Things (IoT) applications in healthcare: 

IoT applications in healthcare are intended not just for healthcare facilities, but also for patients! In a nutshell, IoT in healthcare accomplishes the following tasks:

• reducing the length of time people have to wait at the emergency department
• Keeping track of patients, employees, and inventory
• Improving Drug Management
• ensuring crucial hardware availability

IoT has also offered a number of wearables and devices that have made patients' lives easier. These are the gadgets listed below.

Wearables:

Nowadays, wearables are Bluetooth-enabled, allowing them to connect with your smartphone.

It gives you the ability to filter, equalize, and layer real-world sounds. Doppler Labs is the best illustration of this.

Ingestible sensors:

Ingestible sensors are truly a miracle of contemporary science. These are pill-sized sensors that monitor the medicine in our bodies and alert us if any anomalies are detected.

These sensors can aid diabetic patients by reducing symptoms and providing an early warning of significant health risks. One such example is Proteus Digital Health.

Moodables:

Moodables are mood-enhancing items that help us feel better throughout the day. It may seem like science fiction, but it's not that far off. Thync and Halo Neurosciences have already begun working on it and have made significant progress. Moodables are head-mounted wearables that deliver low-intensity electricity to the brain, therefore elevating our mood.

Computer Vision Technology:

PC Vision Technology, in conjunction with Artificial Intelligence, has resulted in drone innovation, which intends to replicate visual understanding in order to empower dynamic in view of it.

Drones like Skydio employ PC vision technologies to detect obstacles and navigate around them. This invention has also greatly aided externally disadvantaged folks in exploring effectively.

IoT-fueled gadgets lessen a significant part of the manual work. For example, a specialist needs to utilize IoT gadgets during patient graphing. Here, IoT sensors can gauge a wide range of od information, for example, circulatory strain, internal heat level, and so forth, and diagram everything into an application associated with estimation gadgets through IoT.

Furthermore, it makes the patient's information promptly available for audit. Such an IoT application could set aside to 15 hours/seven day stretch of a specialist's manual outlining.

In the age of hyper-connectivity, the Internet of Things (IoT) technology has provided countless innovators the opportunity to build software and hardware for different purposes — from medical smart devices and manufacturing to smart cities and homes. 

According to Statista, 15.9 billion connected devices will be connected worldwide by 2030. The global IoT spending will reach $1.1 trillion the same year. However, the growing number of IoT apps has also increased the amount spent by businesses to recall defective IoT devices.

You see, developing an IoT device is the only step towards ensuring its longevity. It is also essential to conduct proper QA testing to ensure the IoT software is strong enough to withstand security threats, performance malfunction, and connectivity issues. 

Your IoT device should work collaboratively and deliver value to the business as intended at the end of the day. In this article, we will discuss the definition, benefits, process, and types of IoT testing. But first, let us start with the basics: 

What is IoT testing? 

The general IoT network connectivity comprises four core layers, including the physical layer (sensors and controllers), network layer (gateways and communication units), data management layer (local or cloud services at the backend), and the application layer (software for user interaction). 

Since data is heavily transmitted from one object to another over the Internet in the ecosystem, it is vital to verify that your electronic devices can exchange sensitive information easily before the market launch and throughout their lifecycle. 

That is why all successful IoT businesses rely on automation, penetration, and performance testing tools to spot any defect in the IoT device before it reaches the hands of end customers.  

IoT testing is the practice of conducting QA tests to validate the performance, minimize security issues, and boost the functionality of an IoT device. It broadly revolves around device networks, operating systems, security, analytics, platforms, and standards. 

QA testers trace and associate software releases and cycles, test cases and scripts, look for defects, test executions, and gather other requirements. The complexity and variability of IoT testing make planning a crucial aspect of the process. 

The significant benefits of IoT testing 

QA engineers and developers can provide better  service offerings by employing IoT automation testing in their general practices with the right plan and purpose in place. These are the benefits that they can plan to see with IoT testing: 

1. Faster time-to-market 

IoT testing ensures that businesses can launch their safe and approved IoT products in the market by leveraging automation. 

2. Business future-proofing 

IoT testing offers an integrated approach for validating IoT platforms' practical and non-functional testing requirements. The practice future-proofs the business by enabling higher interoperability and security with performance testing tools. In the end, you can deliver safer solutions and, therefore, be a better prospect for consumers. 

3. New business opportunities 

Testing the IoT solutions speeds up innovation with less risk and without delaying the response time or using too many resources. With set testing processes, businesses can experiment much more freely with IoT products in the market with minimal human intervention. 

IoT testing framework 

Given the complexity of IoT solutions, check all layers separately, verify the entire system's operation, and determine the interoperability level of several layers. Please refer to a robust testing framework to ensure the testing is done properly across all software versions. Some fundamental features that should be a part of the framework are listed below: 

1. Performance testing 

It is essential to strategically approach the development and implementation of an IoT testing plan. That is why measure the IoT app's performance metrics such as throughput, CPU utilization, latency, and so on. Validate the stability of the entire app's functioning under changing operational and network conditions such as intermittent failures. 

2. Security testing 

Testing how safe and secure an IoT app functions is paramount. After all, many users access a massive amount of data all the time. You must, therefore, have data privacy controls and validate users via authentication as a part of your security testing processes. 

3. Compatibility testing 

Multiple devices are connected in a typical IoT ecosystem with different software and hardware configurations. Please ensure your IoT product is highly compatible with different tools and platforms for its smooth functioning. 

Use data recorders, for instance, to check out how the recorded data plays across different device end-points automatically and freely. 

4. Device interoperability 

IoT testing ensures that the end customers have a state-of-the-art user experience across multiple channels such as web apps and mobile devices. 

Visualize the required use cases and arrange the testing process. For instance, all layers should be checked for security and functioning separately. Then deploy APIs to review the application and data management layers. Test the physical and network layers for compatibility. 

Seven types of testing tools 

To execute a wide range of IoT tests at the staging phase, use the right automation, visualization, simulation, and measurement tools. Here are the different IoT testing tools that can make a ton of difference to how you approach the process: 

1. Device or protocol simulators 

As the name suggests, these IoT testing tools are often simulated in large numbers and configured to map the required real-time scenarios. The simulators are standards-compliant and support numerous IoT protocols in format testing processes. 

2. Record and playback test automation tools 

These tools are multi-purpose as QA testing teams find them useful in many test scenarios. The assessment involves recording a user's actions and matching objects behind the scenes to identify which units of code are routinely used and how. In this type of testing, a coded test script file is generated, which the QA engineers replay as is. 

3. Mobile testing tools 

These IoT testing tools offer automated functional mobile testing, replicating customer experience and ensuring the IoT app works as expected. 

4. API testing tools 

Integrate an automated API testing tool with your continuous integration pipeline for improving your IoT app's codebase quality. Detect bugs early on in the IoT app development lifecycle with end-user application testing. 

5. Visualization tools 

The real-time validation of the IoT application is difficult and time-consuming. Introducing IoT data visualization tools can help finish the development process faster with minimal dependence in the real-time environment. 

That is because they initiate the cost-friendly and timely execution of compatibility tests without making any hefty investments in the hardware, browsers, platform services, operating systems, and so on. 

6. Automated deployment tools 

Automation testing tools help create virtual machines on the cloud or on-premise for rapidly commissioning managed services and configuring and deploying customized applications and services. Improve speed, productivity, and effectiveness of quality over execution. 

7. Security testing tools 

These can be categorized as static code analysis, threat modeling, and run-time threat-inducing. Unearth vulnerabilities, prioritize them, and offer recommendations on how to fix them with the help of security testing tools. 

The ultimate IoT testing process 

An IoT setup deploys various software testing approaches that are slightly different from the regular QA practices for validating IoT apps. Here is what a typical IoT testing process looks like: 

1. Lay the groundwork with the help of QA engineers 

Assign a QA testing team while the specifications for the IoT application are being decided. Having them on board at the beginning will help them choose how often the IoT development team will need to collaborate with the QA engineers to prioritize relevant test cases, enable regressing testing, and efficiently manage defects. 

They will also confirm the IoT testing risks and design an overall risk mitigation plan for your IoT app development project. Taking the QA team's help ensures proper test automation frameworks and configuration to address quality issues and whatnot. 

2. Prepare for IoT app testing 

Even when the QA team has designed a comprehensive testing strategy, they are still required to regularly revise and update the test artifacts. It would help if you also had a balanced combination of manual and automated testing to make sure the IoT app is error-free and to avoid data- and time-intensive repetitive test cases execution. 

Prepare for conducting different types of testing, including conducting usability testing, simulating sensors, verifying data integrity, determining the end-to-end workflows of the entire IoT application, and flawless communication between various IoT app components with their tech stack compatibility. 

3. Select a vendor for outsourced IoT testing 

If you do not wish to carry out the function in-house, consider outsourcing as it proves to be more cost-effective than hiring a full-time staff. Plus, you have access to a greater talent pool and technological expertise. IoT testing becomes hassle-free. To select a fitting vendor of automation testing tools, please do the following: 

• Shortlist vendors with successful IoT testing projects in your sector. 

• Create a comprehensive request for proposal which includes your IoT solution's specific requirements. 

• Consider their existing tech stack and human resources, so you do not get stuck in the middle of running tests. 

• Understand their approach to an IoT testing strategy, testing toolkit, the planned test automation, and so on. 

4. Launch your IoT tests 

Once you have figured out your resources, it is time to design test cases and build test scripts. Check the end-to-end functioning of the IoT product by creating an IoT test lab with the help of service visualization tools. These labs serve as the digital portfolio for experimenting and simulating real-time experiences that fuel more innovative automation testing tools. 

Over to you 

IoT solutions can be challenging to develop, manage and test given the multiple components and interactions between them. It is, therefore, necessary to monitor the performance of the app more closely with automation testing tools. A thorough testing process ensures a quality IoT product and high customer satisfaction. So, how do you plan to get started with IoT testing?