Original article is published at Forbes: link
Have heard about the magic pill? Not sure how it works, but it helps you lose 20 pounds in a week while consuming the same calories as before. And you’ve probably also heard about the scary side effects of that pill. The need for magic pills is appearing in the IoT market as well. Thanks to the explosion of sensors to measure everything imaginable within the Internet of Things, enterprises are confronted with a never-ending buffet of tempting data.
Typically data has been consumed like food: first it is grown, harvested, and prepared. Then this enjoyable meal is ingested into a data warehouse and digested through analytics. Finally we extract the nutritional value and put it to work to improve some part of our operations. Enterprises have evolved to consume data from CRM, ERP, and even the Web that is high in signal nutrition in this genteel, managed manner from which they can project trends or derive useful BI.
The IoT and its superabundance of sensors completely changes that paradigm and we need to give serious consideration to our data dietary habits if we want to succeed in this new data food chain. Rather than being served nicely prepared data meals, sensor data is the equivalent of opening your mouth in front of some kind of cartoon food fire hose. Data comes in real-time, completely raw, and in such sustained volume that all you can do is keep stuffing it down.
And, as you would expect, your digestion will be compromised. You won’t benefit from that overload of raw IoT data. In fact, we’ll need to change our internal plumbing, our data pipelines, to get the full nutritional benefit of IoT sensor data.
That will require work, but if you can process the data and extract the value, that’s where the real power comes in. In fact, you can attain something like superpowers. You can have the eyesight of eagles (self-driving cars), the sonar wave perception of dolphins (for detecting objects in the water), and the night vision of owls (for surveillance cameras).If we can digest all this sensor data and use it in creative ways, the potential is enormous. But how can we adapt to handle this sort of data? Doing so demands a new infrastructure with massive storage, real-time ingestion, and multi-genre analytics.
If we can digest all this sensor data and use it in creative ways, the potential is enormous. But how can we adapt to handle this sort of data? Doing so demands a new infrastructure with massive storage, real-time ingestion, and multi-genre analytics.
Massive storage. More than five years ago, Stephen Brobst predicted that the volume of sensor data would soon crush the amount of unstructured data generated by social media(remember when that seemed like a lot?). Sensor data demands extreme scalability.
Real-time ingestion. The infrastructure needs to be able to ingest raw data and determine moment by moment where to land it. Some data demands immediate reaction and should move into memory. Other data is needed in the data warehouse for operational reporting and analytics. Still other data will add benefit as part of a greater aggregation using Hadoop. Instant decisions will help parse where cloud resources are appropriate versus other assets.
Multi-genre analytics. When you have data that you’ve never seen before, you need to transform data and apply different types of algorithms. Some may require advanced analytics and some may just require a standard deviation. Multi-genre analytics allows you to apply multiple analytics models in various forms so that you can quickly discern the value of the data.
The self-driving car is a helpful metaphor. I’ve heard estimates that each vehicle has 60,000 sensors generating terabytes of data per hour. Consider the variety of that data. Data for obstacle detection requires millisecond response and must be recognized as such if it is to be useful. A sensor on the battery to predict replacement requires aggregation to predict a trend over time and does not require real-time responsiveness. Nevertheless both types of data are being created constantly and must be directed appropriately based on the use case.
How does this work at scale? Consider video games. Real-time data is critical to everything from in game advertising, which depends on near instant delivery of the right ad at a contextually appropriate moment, to recommendations and game features that are critical to the user experience and which are highly specific to moments within the game. At the same time, analyzing patterns at scale is critical to understanding and controlling churn and appeal. This is a lot of data to parse on the fly in order to operate effectively.
From a data perspective, we’re going to need a new digestive system if we are to make the most of the data coming in from the IoT. We’ll need vision and creativity as well. It’s an exciting time to be in analytics.
The technology sector is buzzing with predictions and hype about the Internet of Things (IoT), but many people are still confused about what it means, what the real world opportunities are and why businesses should be looking into IoT.
At a fundamental and simplistic level the Internet of Things refers to 'physical objects which linked via wired or wireless networks'
These physical objects could be anything (such as medical machines, vehicles, building systems, signage, toasters, smoke alarms, temperature sensors, weather monitors, intelligent tags or rubbish bins for example). Almost any object, in any sector, in any location could potentially join the Internet of Things, so its no wonder that Gartner predict there will be 50 billion devices connected by 2020 (and other analysts estimate several orders of magnitude more).
Typically the Internet of Things is used to gather data and insight, find efficiency, automate tasks or improve an experience or service. At Smarter Technology Solutions (STS) we put this down to a simple formula, with greater insight, comes better decisions.
I know what you're thinking, why would you connect an object like a rubbish bin to the Internet?
Well its a simple example but it has tremendous flow on effects. Simply tracking the fill level of a rubbish bin using a smart sensor, councils and waste providers can find out a few important facts such as fill-level trends, how often the bin really needs emptying and when, to better plan waste collection services (eg timing of bin collection near food outlets to avoid lunchtimes) and to identify areas that may need more/less bins (to assist with city/service planning).
By collecting just the fill level data of a waste bin the following benefits could be attained:
- Reduction in cost as less bin collections = less waste trucks on the road, no unnecessary collections for a bin that's 20% full, less labour to complete waste collection. This also provides a level of operational efficiency and optimized processes.
- Environmental benefit - where waste is not overflowing and truck usage is reduced, flow on environmental impact, pollution and fuel consumption is minimized. By ensuring waste bins are placed in convenient locations, littering and scattered waste is also minimized.
- Service improvements - truck collection routes can be optimized, waste bins can be collected at convenient times and planning of future/additional services can be amended as the data to trend and verify assumptions is available.
More complex examples of IoT include:
- Intelligent transport systems which update digital signage on the highway and adjusts the traffic lights in real time to divert traffic, optimise traffic flow and reduce congestion;
- A farm which uses sensors to measure soil moisture, chemical levels and weather patterns, adjusting the watering and treatment schedules accordingly;
- The building which draws the blinds to block out the afternoon sun, reducing the need to consume more power cooling the building and to keep the environment comfortable;
- Health-care devices which monitor patients and auto-alert medical practitioners once certain symptoms or attributes are detected;
- Trucks which automatically detect mechanical anomalies and auto schedule themselves in for preventative maintenance once they reach certain thresholds;
- Asset tracking of fleet vehicles within a services company which provides operations staff with fleet visibility to quickly dispatch the closest resource to a job based on proximity to the next task;
- Water/gas/electric meters which sends in their own reading in on a monthly basis and trends analysis which can detect potential water/gas leaks; or
- A retail store which analyses your in-store behavior or purchasing patterns and recommend products to you based on previous choices and your personal preferences.
At Smarter Technology Solutions we specialize in consulting with organizations to understand the benefits of IoT, design best fit solutions, engineer and implement solutions as well as supporting the ongoing support needs of the organization. This results in 3 key outcomes:
- Discovery of New Opportunities - With better visibility, trends, opportunities, correlations and inefficiencies can be understood. From this, products, services and business models can be adjusted or changed to achieve competitive advantage.
- Improved Efficiency - By identifying inefficiencies in existing business practices, work-flows can be improved and more automated services can be provided.
- Improved Services - With trends and real time data businesses are able make smarter decisions and alter the way you services are delivered.
The Internet of Things is changing the world, heralded as one of the most pivotal technology trends of the modern era. We are getting ready to enter a time where everything, quite literally, is connected to the Internet.
For the industrial sector, this is a new area of exploration. Factories have smart infrastructures that use sensors to relay data about machine performance. Cities have smart grids that monitor everything from traffic to the energy used by streetlights. Hospitals can monitor the health of high-risk, at-home patients.
In other words, we are entering a hacker's dream world.
Recent attacks, like the Christmas 2015 attack on the Ukraine power grid, have shown that the Internet of Things possesses severe vulnerabilities. These weak points can be everything from back doors that allow a hacker access to a system to lack of proper use by untrained workers. If your business uses IoT devices, there’s a good chance they are not secure.
Why are so many systems left vulnerable? Weaknesses often come from the same set of five drivers:
Whether your company is struggling because your devices were deployed too quickly or operational costs constraints got in the way, your team must take measures to fix security risks. Here are four security flaws:
1. Lack of Encryption
Any device that is connected to the Internet to relay data needs encryption. When communication between devices and facility machines are now encrypted, it provides a doorway for hackers to send malicious updates, steal data, and even take control of the system.
In 2014, an Israeli security firm took control of cars using a specific connected telematics device that failed to use proper encryption.
2. Failing to Install Updates
Once you have a machine-to-machine communication system working properly, it can be easy to forget to install the necessary updates to keep the network secure.
Yet, hackers are constantly updating their strategies and tactics. Failing to install updates and patches leaves your system vulnerable.
Even if you’re worried about breaking integrations between systems, you should at the least install every security update released by the vendor. These updates are specifically designed to address vulnerabilities discovered in your devices. After all, if your vendor releases a security update, it’s because they found a problem.
You also should know that updates and patches are not always the final solution to security vulnerabilities. Unfortunately, many manufacturers are not able or willing to provide the necessary support to continue updating their devices.
To avoid this risk, shop carefully for systems that provide updates and are backed by a trusted company.
3. Poorly Built Networks
The modern industrial network is designed to get tasks done. If the design focuses too much on completing that task, it will leave weak points in security. Things that are obvious when building IT networks are sometimes less obvious when creating industrial DNP3 and other network architecture.
The solution to this risk is fairly simple. Those tasked with building industrial networks need to ensure they are partnering with IT professionals to build networks that are safer from attacks. Security features, like deep packet inspection and network segmentation, should be in place from the beginning.
4. Sensors Outside of the Company's Control
Most of the sensors and other connected pieces that make up a network are controlled by the company. But for some companies, that is not the case. For example, power companies have sensors in their customer's homes.
Sensors outside of the company's immediate control are hard to secure, which gives hackers access. Currently, cloud-based security using public key services to authenticate devices may be the best solution to this problem.
Don't Take The Risk
Industrial security breaches can cause devastating consequences. Therefore, the above risks need to be addressed.
As more industrial facilities rely on the Internet of Things, it's important for company teams to be aware of the potential vulnerabilities. Take security into full consideration.
The Internet of Things (IoT) concept promises to improve our lives by embedding billions of cheap purpose-built sensors into devices, objects and structures that surround us (appliances, homes, clothing, wearables, vehicles, buildings, healthcare tech, industrial equipment, manufacturing, etc.).
IoT Market Map -- Goldman Sachs
What this means is that billions of sensors, machines and smart devices will simultaneously collect volumes of big data, while processing real-time fast data from almost everything and... almost everyone!!!
IoT vision is not net reality
Simply stated, the Internet of Things is all about the power of connections.
Consumers, for the moment anyway, seem satisfied to have access to gadgets, trendy devices and apps which they believe will make them more efficient (efficient doesn't necessarily mean productive), improve their lives and promote general well-being.
Corporations on the other hand, have a grand vision that convergence of cloud computing, mobility, low-cost sensors, smart devices, ubiquitous networks and fast-data will help them achieve competitive advantages, market dominance, unyielding brand power and shareholder riches.
Global Enterprises (and big venture capital firms) will spend billions on the race for IoT supremacy. These titans of business are chomping at the bit to develop IoT platforms, machine learning algorithms, AI software applications & advanced predictive analytics. The end-game of these initiatives is to deploy IoT platforms on a large scale for;
- real-time monitoring, control & tracking (retail, autonomous vehicles, digital health, industrial & manufacturing systems, etc.)
- assessment of consumers, their emotions & buying sentiment,
- managing smart systems and operational processes,
- reducing operating costs & increasing efficiencies,
- predicting outcomes, and equipment failures, and
- monetization of consumer & commercial big data, etc.
IoT reality is still just a vision
No technology vendor (hardware or software), service provider, consulting firm or self-proclaimed expert can fulfill the IoT vision alone.
Recent history with tech hype-cycles has proven time and again that 'industry experts' are not very accurate predicting the future... in life or in business!
Having said this, it only makes sense that fulfilling the promise of IoT demands close collaboration & communication among many stake-holders.
A tech ecosystem is born
IoT & Industrial IoT comprise a rapidly developing tech ecosystem. Momentum is building quickly and will drive sustainable future demand for;
- low-cost hardware platforms (sensors, smart devices, etc.),
- a stable base of suppliers, developers, vendors & distribution,
- interoperability & security (standards, encryption, API's, etc.),
- local to global telecom & wireless services,
- edge to cloud networks & data centers,
- professional services firms (and self-proclaimed experts),
- global strategic partnerships,
- education and STEM initiatives, and
- broad vertical market development.
I'll close with one final thought; "True IoT leaders and visionaries will first ask why, not how..!"
Editors Note: Members of IoT Central are encouraged to participate in Ventana Research's study. The author of the blog shares details below.
The emerging Internet of Things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any device can generate and transmit data about its operations – data to which analytics can be applied to facilitate monitoring and a range of automatic functions. To do these tasks IoT requires what Ventana Research calls operational intelligence (OI), a discipline that has evolved from the capture and analysis of instrumentation, networking and machine-to-machine interactions of many types. We define operational intelligence as a set of event-centered information and analytic processes operating across an organization that enable people to use that event information to take effective actions and make optimal decisions. Ventana Research first began covering operational intelligence over a decade ago.
In many industries, organizations can gain competitive advantage if they reduce the elapsed time between an event occurring and actions taken or decisions made in response to it. Existing business intelligence (BI) tools provide useful analysis of and reporting on data drawn from previously recorded transactions, but to improve competitiveness and maximize efficiencies organizations are concluding that employees and processes in IT, business operations and front-line customer sales, service and support also need to be able to detect and respond to events as they happen.
Both business objectives and regulations are driving demand for new operational intelligence technology and practices. By using them many activities can be managed better, among them manufacturing, customer engagement processes, algorithmic trading, dynamic pricing, yield management, risk management, security, fraud detection, surveillance, supply chain and call center optimization, online commerce and gaming. Success in efforts to combat money laundering, terrorism or other criminal behavior also depends on reducing information latency through the application of new techniques.
The evolution of operational intelligence, especially in conjunction with IoT, is encouraging companies to revisit their priorities and spending for information technology and application management. However, sorting out the range of options poses a challenge for both business and IT leaders. Some see potential value in expanding their network infrastructure to support OI. Others are implementing event processing (EP) systems that employ new technology to detect meaningful patterns, anomalies and relationships among events. Increasingly, organizations are using dashboards, visualization and modeling to notify nontechnical people of events and enable them to understand their significance and take appropriate and immediate action.
As with any innovation, using OI for IoT may require substantial changes to organizations. These are among the challenges they face as they consider adopting this evolving operational intelligence:
- They find it difficult to evaluate the business value of enabling real-time sensing of data and event streams using radio frequency identification (RFID) tags, agents and other systems embedded not only in physical locations like warehouses but also in business processes, networks, mobile devices, data appliances and other technologies.
- They lack an IT architecture that can support and integrate these systems as the volume, variety and frequency of information increase. In addition, our previous operational intelligence research shows that these data sources are incomplete or inadequate in nearly two out of five organizations.
- They are uncertain how to set reasonable business and IT expectations, priorities and implementation plans for important technologies that may conflict or overlap. These can include BI, event processing, business process management, rules management, network upgrades, and new or modified applications and databases.
- They don’t understand how to create a personalized user experience that enables nontechnical employees in different roles to monitor data or event streams, identify significant changes, quickly understand the correlation between events and develop a context adequate to enable determining the right decisions or actions to take.
Today’s fast-paced, 24-by-7 world has forced organizations to reduce the latency between when transactions and other data are recorded and when applications and BI systems are made aware of them and thus can take action. Furthermore, the introduction of low-cost sensors and the instrumentation of devices ranging from appliances and airline engines to crop management and animal feeding systems creates opportunities that have never before existed. Technological developments such as smart utility meters, RFID and embedded computing devices for environmental monitoring, surveillance and other tasks also are creating demand for tools that can provide insights in real time from continuous streams of event data.
As organizations expand business intelligence to serve operational needs by deploying dashboards and other portals, they are recognizing the need to implement technology and develop practices that collect events, correlate them into meaningful patterns and use workflow, rules and analytics to guide how employees and automated processes should react. In financial services, online commerce and other industries, for example, some organizations have built proprietary systems or have gone offshore to employ large teams of technicians at outsourcing providers to monitor transactions and event streams for specific patterns and anomalies. To reduce the cost, complexity and imperfections in these procedures, organizations now are seeking technology that can standardize and automate event processing and notify appropriate personnel of significant events in real time.
Conventional database systems are geared to manage discrete sets of data for standard BI queries, but event streams from sources such as sensing devices typically are continuous, and their analysis requires tools designed to enable users to understand causality, patterns, time relationships and other factors. These requirements have led to innovation in event stream processing, event modeling, visualization and analytics. More recently the advent of open source and Hadoop-related big data technologies such as Flume, Kafka, Spark and Storm are enabling a new foundation for operational intelligence. Innovation in the past few years has occurred in both the open source community and proprietary implementations.
Many of the early adopters of operational intelligence technologies were in financial services and intelligence, online services and security. However, as organizations across a range of other industries seek new competitive advantages from information or require real-time insight for risk management and regulatory compliance, demand is increasing broadly for OI technologies. Organizations are considering how to incorporate event-driven architectures, monitor network activity for significant event patterns and bring event notification and insight to users through both existing and new dashboards and portals.
To help understand how organizations are tackling these changes Ventana Research is conducting benchmark research on The Internet of Things and Operational Intelligence. The research will explore how organizations are aligning themselves to take advantage of trends in operational intelligence and IoT. Such alignment involves not just information and technology, but people andprocesses as well. For instance, IoT can have a major impact on business processes, but only if organizations can realign IT systems to a discover-and-adapt rather than a model-and-apply paradigm. For instance, business processes are often outlined in PDF documents or through business process systems. However, these processes are often carried out in an uneven fashion different from the way the model was conceived. As more process flows are directly instrumented and some processes carried out by machines, the ability to model directly based on the discovery of those event flows and to adapt to them (either through human learning or machine learning) becomes key to successful organizational processes.
By determining how organizations are addressing the challenges of implementing these technologies and aligning them with business priorities, this research will explore a number of key issues, the following among them:
- What is the nature of the evolving market opportunity? What industries and LOBs are most likely to adopt OI for IoT?
- What is the current thinking of business and IT management about the potential of improving processes, practices and people resources through implementation of these technologies?
- How far along are organizations in articulating operational intelligence and IoT objectives and implementing technologies, including event processing?
- Compared to IT management, what influence do various business functions, including finance and operations management, have on the process of acquiring and deploying these event-centered technologies?
- What suppliers are organizations evaluating to support operational intelligence and IoT, including for complex event processing, event modeling, visualization, activity monitoring, and workflow, process and rules management?
- Who are the key decision-makers and influencers within organizations?
Please join us in this research. Fill out the survey to share your organization’s existing and planned investments in the Internet of Things and operational intelligence. Watch this space for a report of the findings when the research is completed.
SVP & Research Director
Home Automation DIY Case Study
The following is from a Mind Commerce interview with residential owner/installer/operator:
“ I got into the home automation craze by accident when one of my managers described what he was doing. After looking at it, the added convenience, security, and cost savings made me a believer. The overall category of devices that I use are the Internet of Things (IoT). ”
“ My setup is as follows:
- I have an Amazon Echo that allows me to issue voice commands to the majority of my IoT devices. It also will play music from my Amazon Prime account and allow me to order merchandise (all voice of course). It additionally allows me to keep a TODO and shopping list that is synchronized to my Alexa app on my iPhone. As I think of items, I just tell Alexa (the name for the Echo), and she will add the items to the list. I use this all the time. You can also set timers and alarms vocally, which is another well-used feature. There's tons more. The Echo talks WiFi.
- I use a Wink Hub to interface the Echo to devices that don't directly talk over WiFi, or that the Echo doesn't directly support. The Wink Hub talks Z-Wave, Zigbee, WiFi, and Lutron's proprietary communications (dimmers). The Wink Hub also has a nice APP that lets me control everything directly from my cellphone if I want.
- I use Luton dimmers that allow me to turn on, turn off, or set the dimming level for my most commonly used lights. The echo supports this so I can say "Alexa set living room lights to XX%" and it happens.
- I have a Rain Machine which is a connected sprinkler controller. I can turn on stations from the Echo, but I don't. What it allows me to do is to set the watering parameters and then it connects to NOAA and it will modify my preferences based on how much rain has fallen. Money saver. It has a great APP and will tell me how much each station actually watered per week. A real money saver in Florida.
- The Ecobee 3 thermostat was an expensive but awesome IoT purchase that also saved me a lot of money this past winter. It is very smart and connects to the Echo directly (WiFi). I can tell Alexa to raise or lower the temperature by voice. Setup couldn't be any simpler, and the APP is awesome. Conventional wisdom in the winter is to lower your temperature at night and then have it increase before you wake to save money. Wrong! The Ecobee tracks when your fan and compressor run (view on the website). I found out that turning the temperature down by 4 degrees overnight was causing my heat strips (expensive) to turn on for a couple of hours around 5AM to bring the temperature back up. I was much better off just leaving it one degree less all the time.
- For my garage door controller, I bought an IoT box that allows me to view the status of the garage door and to remotely open or close the door by using the Wink APP. Really nice when I can't remember if I closed the door, or left it open. This doesn't work with the Echo by design (having a crook yell into your house "Alexa open the garage door" wouldn't be a good thing).
- Nest Cam is an awesome security device. When I'm on travel I can view what's going on in the house and even hear what's going on. It's got 1080p resolution and night IR capability (see at night with the lights off). I can even talk to my cat through it. I pay for the cloud recording service, so when it's on, a month of recording is held on the cloud, which would be useful if the house is ever robbed. The problem is I don't want it recording while I'm home. That is solved by...
- Leviton makes smart bricks that plug into an outlet and let you plug an appliance (anything) into it and control that appliance on/off state through Wink or the Echo. So when I leave, I can just vocally tell the Nest Cam to turn on, or if I forget, I can just use the Wink APP to turn it on remotely. I use these to control the Nest Cam, my DirecTV internet device, and my Amazon Fire TV. Whey have them sucking energy all the time when I use them maybe 2% of the time? “
As an advanced user*, he also had this to say:
- “ The is a function call IFTT (If This Then That) that works with the Echo, Wink and the IoT devices to allow creation of recipes that handle what to do if something happens. For example, I set up an IFTT that when I ask the Echo where my cellphone is, the IFTT will call the phone so it rings. The possibilities are limitless. Think Geo-fencing or linking input from IoT sensors to automatically cause actions. “
*Note: Remember, this is a more advanced, tech user. However, IoT is increasingly becoming part of the consumer lexicon!!
- Mercedes-Benz models introduced this year can link directly to Nest, the Internet of Things powered smart home system, to remotely activate a home’s temperature controls prior to arrival.
- Audi has developed a 12.3 inch, 3d graphics fully digital dashboard in partnership with NVIDIA.
- Telematics Company OnStar can shut down your stolen car remotely helping police solve the case.
- ParkMe covers real time dynamic parking information and guide drivers to open parking lots and meters. It if further integrating with mobile payments.
What options do you have for remotely monitoring Water and Fluids with Industrial IoT sensor telemetry?
IIoT or Industrial IoT (Internet of Things) is everywhere. It’s across all industries, from high tech transport, to natural resources and governments. IIoT software and hardware is deployed for numerous, varying applications, and it’s critical to understand just what the customer needs. Especially since the customer can’t always articulate exactly what the remote monitoring and sensor telemetry should do. According to a study performed by Verizon: the worldwide Internet of Things market spend will grow from $591.7 billion in 2014 to $1.3 trillion in 2019. That’s tremendous.
One of the areas that we’ve seen recent growth is water and fluid monitoring. Water comes to us as a life sustaining asset and also as a force of destruction. The utility of water needs to be measured and monitored in order to effectively and efficiently use our greatest natural resource. Similarly, monitoring the destructive force of water can be just as important. Let’s talk about the different ways that you can measure and monitor water!
Flow meters calculate the amount of water that flows through them. Flow meters are everywhere from your house to your office, to anywhere and everywhere water is used. Measuring water flow is a need recognized across industries, from agriculture to commercial, pharmaceuticals, and oil and gas. Flow meters in an IIoT solution provide not only a total flow amount, but allow you to utilize real time data to predict and adjust consumption. Further still, real time analysis allows immediate recognition of catastrophic events such as a burst pipe. The analysis will be drawn out further to establish predictive failure behavior and potentially prevent massive water loss issues like the ones that happened in Los Angeles and Hollywood Hills.
Almost certainly this one is all about protecting assets. There are essentially four ways that we have used to detect presence, quantity, volume, and levels of water. Each of these fits quite well for a particular purpose. They also compliment each other nicely!
Presence of Water: The Rope Sensor
Rope sensors are great and they come in a variety of lengths. A rope sensor will tell you if you have water present at any point along the sensor. Imagine a large trailer with rope sensors running along the bottom of the trailer. If you have a spill in that trailer, truck, or vehicle and any fluid reaches the rope sensor, then you’ll receive an alert and immediately know there’s a problem.
Rope sensors are also great for flood detection. Because you can purchase these sensors in practically any length, you can lay them across a flood channel. If any portion of that rope sensor gets wet then you know you have water present. However, in terms of flood detection rope sensors will tell you if there is water, but they won’t tell you how much.
Presence of Water: Yes or No
If your rope sensor went off on a flood channel you might want to know how much water is flowing through. Depending on the lay of the land there are a number of different applications that we use to provide this information.
Ultrasonic, Ultrasound, Pulse, and Radar Sensors
If you have a fixed structure next to or going over a flood channel then a great solution is an ultrasonic sensor. Essentially, once the sensor is fixed in place it will continuously ping the ground. When the reading between the sensor and the ground becomes more compact, you can calculate that distance and in turn determine how much water is flowing through the channel and the flood level. Also note that radar and ultrasonic fluid level sensors are quite useful for remotely monitoring levels and volumes of liquid products in assets like tanks!
Another way that we have measured quantity of water is by using a pressure transducer. A sensor with a membrane sits at the bottom of a water well, lake, or a reservoir, or a flood channel. As the water increases above the sensor so does the pressure on the sensor’s membrane. The higher the pressure the more water you have moving through!
Making things Digital
Water metering and water detection are now all IIoT solutions. All of these meters / sensors connect to sensor hub connector hardware that sends data out into the internets and into a cloud data analysis solution. Whether you’re monitoring agriculture / viticulture, oil / gas / mining, municipal water treatment facilities or other water plants, nowadays you can obtain a cost-effective, rapidly deployable monitoring solution.
I recently shared the Top 10 Books to Read Now on IoT. In an attempt to keep everyone smarter and share resources in the most simple way, I created the ever ubiquitous listicle by compiling what I believe are the Top 50 IoT people to follow on Twitter. These are, as far as I can tell, real people and not brands.
How did I compile this list? No hard data science here, just good old grunt work from researching, reading and talking with people over the last few months. If you have any suggestions or if I missed an important person, please leave a comment. Or better yet, tweet to me @DavidOro.
If you make it to the bottom of this list, I provide an easy way for you to follow them all with just one click.
Without further adieu, the Top 50 in no particular order.
@gigastacey - Stacey Higginbotham. OK, I put Stacey Higginbotham first on purpose cause I like her and for the fact that she’s been reporting on IoT or years and also hosts the popular podcast iotpodcast.com
@Kevin_Ashton Credited with coining the term “Internet of Things”
@mjcavaretta Michael Cavaretta, Manager, Connected Vehicle Analytics, Ford Motor Co.
@chrismatthieu Chris Matthieu, Director IoT Engineering at Citrix
@CB_Telzerow Alex Telzerow, Editor-in-Chief COMPUTER BILD
@timoelliott Timo Elliott, Innovation Evangelist at SAP
Here are a few thoughts from @dataguild on IoT as applied to Data Science. Thanks to @MacSlocum, @JonBruner and the @OReillySolid crew for a great show in San Francisco last month.
At IoT Central we aim to cover all things industrial and IoT. Our site is segmented into five channels: Platforms, Apps & Tools, Data, Security and Case Studies. If you’re going to connect everything in the world to the Internet you should expect to cover a lot. That means plenty of reading, sharing and discussing.
To tackle the reading part we reached out to our peers and friends and put together the 10 best books to read now on IoT. From theoretical to technical, we tried to find the most important and current reading while throwing in one or two relevant classics.
Below is the list we compiled. What books would you recommend?
By Bruce Sterling
I first came across Bruce Sterling’s name when he wrote the November 1996 Wired cover story on Burning Man. I happened to attend the desert arts festival for the first time that year and Bruce’s prose nailed the the experience. I’ve been a fan of his ever since. "Shaping Things is about created objects and the environment, which is to say, it's about everything," says Bruce. This is a great higher level book that looks at the technosocial transformation needed to understand our relationship between the Internet of Things and the environment in which it exists.
By Renee DiResta, Brady Forrest, Ryan Vinyard
Consumer Internet startups seem to get all the media ink these days - think AirBnB, Instagram, What’sApp, Uber. But many forget that much of the technological innovation began with hardware - think Fairchild Semiconductor, Xerox PARC and the stuff that came out of IBM. With an emphasis on ‘Things,’ IoT is set to usher in a new era of hardware startups and any entrepreneur in this space should find this book to be a valuable read.
By Harald Nauman
If IoT devices can’t communicate, you’re not going to get much use out of them. Someone pointed me to Harald Naumann’s book IOT/M2M Cookbook. Harold is an M2M evangelist with a primary interest in implementation of wireless applications. His blog is chocked full of technical tips on wireless communications.
Last week Tom Davenport, a Distinguished Professor at Babson College, wrote about “GE’s Digital Big Swing” in the Wall Street Journal. As he cites in his latest piece, there are many others taking big swings in digital and IoT overall. (BTW - If you’re not following Tom, you really should do so now. His thoughts are a perfect mix of research and practice covering big data, analytics and changes in the digital landscape.)
During my time at Pivotal, I was witness to the digital big swing that GE took and saw the energy, effort and resources they were committing to make sure that whatever they made that could be connected to the Internet - jet engines, power plants, surgical image machines - would capture all data to improve products and the customer experience. I don’t think GE watchers - investors, competitors, partners - fully understand yet the enormity of this bet.
They keep making moves. This week the company announced the creation of GE Digital, a transformative move that brings together all of the digital capabilities from across the company into one organization.
Jeffrey Immelt, Chairman and CEO of GE, said, “As GE transforms itself to become the world’s premier digital industrial company, this will provide GE’s customers with the best industrial solutions and the software needed to solve real world problems. It will make GE a digital show site and grow our software and analytics enterprise from $6B in 2015 to a top 10 software company by 2020.”
GE, the industrial giant, a Top 10 software company? That’s taking GE’s slogan “Imagination at Work” and making it real.
Much like the cloud trend before it, the IoT trend is something where all major vendors are investing.
Yesterday at Salesforce’s behemoth customer conference Dreamforce, the company announced the Salesforce Internet of Things Cloud. Based on a home-grown data processing technology called Thunder, Salesforce touts their IoT Cloud as empowering businesses to connect data from the Internet of Things, as well as any digital content, with customer information, giving context to data and making it actionable—all in real-time.
With perhaps a nod of guilt to marketing hype, other notable big swings include:
IBM - The company has created an Internet of Things business unit and plans to spend $3 billion to grow its analytics capabilities so that organizations can benefit from the intelligence that connected devices can provide. According to IBM, as much as 90 percent of data that is generated by connected devices is never acted on or analyzed.
Cisco - Its approach focuses on six pillars for an IoT System - network connectivity, fog computing, security, data analytics, management and automation and an application enablement platform. You can buy all the pieces of the system from Cisco, of course.
Monsanto - Their near billion dollar purchase of The Climate Corporation is combining The Climate Corporation’s expertise in agriculture analytics and risk-management with Monsanto’s R&D capabilities, and will provide farmers access to more information about the many factors that affect the success of their crops.
In the wake of these giant big swings will be new and exciting startups - sensor companies, chip players, software, analytics and device makers. If you know of a compelling start-up in the industrial IOT space, drop me a line at [email protected]. We would love to hear from you.
You would think that in this day and age of infographics that finding a map laying out the ecosystem of the Internet of Things would exist. Surprisingly, a Google search doesn’t appear to return much. Neither does a Twitter a search.
Recently though I found two worth sharing. One from Goldman Sachs and the other from Chris McCann which I found very interesting - A Map of The Internet of Things Market.
Goldman Sachs’ map is pretty generic but it takes IoT related items all the way from the consumer to the Industrial Internet. In a September 2014 report, “The Internet of Things: Making sense of the next mega-trend”, Goldman states that IoT is emerging as the third wave in the development of the Internet. Much of what we hear about today are on the consumer end of the spectrum - early simple products like fitness trackers and thermostats. On the other end of the spectrum, and what I think IoT Central is all about, is the Industrial Internet. The opportunity in the global industrial sector will dwarf consumer spend. Goldman states that industrial is poised to undergo a fundamental structural change akin to the industrial revolution as we usher in the IoT. All equipment will be digitized and more connected and will establish networks between machines, humans, and the Internet, leading to the creation of new ecosystems that enable higher productivity, better energy efficiency, and higher profitability. Goldman predicts that IoT opportunity for Industrials could amount to $2 trillion by 2020.
Chris McCann, who works at Greylock Partners, has an awesome map of the Internet of Things Market (below). This is what venture capitalists do of course - analyze markets and find opportunities for value by understanding the competitive landscape. This map is great because I think it can help IoT practitioners gain a better understanding of the Internet of Things market and how all of the different players fit together.
The map is not designed to be comprehensive, but given the dearth in available guidance, this is a great starting point. The map is heavily geared towards the startup space (remember the author is a VC) and I think he leaves out a few machine-to-machine vendors, software platforms and operating systems.
Other maps I found that are interesting are:
Thingful, a search engine for the Internet of Things. It provides a geographical index of connected objects around the world, including energy, radiation, weather, and air quality devices as well as seismographs. Near me in earthquake prone Northern California I of course found a seismograph, as well as a weather station, and an air quality monitoring station.
Shodan, another search engine of sorts for IoT.
And then there is this story of Rapid7’s HD Moore who pings things just for fun.
If you have any maps that you think are valuable, I would love for you to share them in the comments section.
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