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To monetize any engagement or a project, data is a critical element. Data needs to be cleaned, aggregated, ingested, modeled and analyzed to provide business insights which are actionable. A project which is addressing defined business use case would be meaningful if it provides us insights. IoT projects are multi-dimensional, they cover layers like Device - Device, Device-Server, and Server-Server when it comes to data and its flow .

A typical project in  IoT gets represented as a complex system of networks, platforms, interfaces, protocols, devices, and data. IoT devices range from sensors, actuators, gateways, and embedded hardware/software within products and assets.

The number and type of IoT devices, as well as the associated use cases for apps and services, will grow exponentially within leading industry verticals. One of the critical success factors for IoT operation which could well be termed as Operational Support Systems (OSS) for IoT is  IoT Device Management.

If devices are not managed well , the output data would be a suspect and the project could well be a failed one. The need for IoT device management is paramount and it could be a matter of concern or an opportunity to differentiate as well if addressed with care

Fundamentally IoT Device Management would cover areas like

  1. Provisioning and Authentication
  2. Configuration and Control
  3. Software Updation and Maintenance
  4. Monitoring and Diagnostics

I would not slot Security here as it is a separate subject in its own way.

Of the 4 areas listed 1, 2 and 3 can be done with a degree of control as we initiate the project. The last point of Monitoring and Diagnostics is the most critical as the level of control which needs to be brought in, is the most complex. This is given the diversity and the scale in terms of a number of devices, the corresponding protocols, the associated challenges of interoperability. Then there is the need to replicate the problems and take corrective or predictive actions.

Data may have the flamboyance of a hero in the IoT story, but the real workhorses are the devices which work at the edge of the IoT system—the “Things" in the Internet of Things” . The devices spew out the data and hence a healthy device would provide honest data.

Devices out in the field are either generating and transmitting data to a centralized platform ( one-way movement) or performing automated tasks that generate data. A mundane job, perhaps, yet the overall performance of a system often hinges on the health of field devices.

Imagine running a critical operation of managing a fleet of trucks managing a cold chain shipping perishable goods. If a device, sensor, embedded agent, or gateway begins to falter, and more importantly has not been monitored well enough and corrective actions not taken,  the consequences could be  dire  and contractual impact could be disastrous .

The challenge of maintaining devices may sound basic compared with aggregating and analysing data, but it’s essential to a successful IoT strategy.

  • So what is the factor which make the devices vulnerable and hence the output data could be unreliable?

The key factor here is RF Technology .

Most IoT devices rely on radio frequency (RF) technology such as Bluetooth, ZigBee and Wi-Fi for communications. Otherwise known as far-field transmission, RF is great when communicating over long distances, but becomes problematic when applied to short-range, isolated IoT ecosystems, like the wireless personal area network.

Link and network security become increasingly difficult as the number of any RF devices increases as per research reports. The relentless requirement for decreasing power consumption in devices translates to less room for handshake and encryption protocols. These issues are clearly reflected by Bluetooth’s increasingly poor reliability and security record.

Then it is seen that RF-based devices are shutting each other down due to interference, a situation that will grow worse when the IoT industry grows by the billions.

  • So how would these vulnerabilities get addressed?

An alternative which will come mainstream is  Near Field Magnetic Induction (NFMI) for RF. NFMI uses the modulations of magnetic fields to transfer data wirelessly between two points. Its main strength is its attenuation. It decays a thousand times faster than RF signals, which eliminates much of the interference and security issues that are attributed to technologies such as Bluetooth.

NFMI will prove its worth in a new way in the age of IoT as it marches to mainstream adoption.

  • How will Operational Support System metamorphose?

As devices explode in numbers human cannot control a billion nodes connected in a wide-area however centralized the remote based management it may be .

Here the deployment of machine learning for the development of a dynamic, automated network management framework would be key. Industry is coming up with proprietary algorithms to provides real-time distributed system control and self-management and self-healing capabilities for huge long-range IoT networks consisting of billions of smart devices and sprawling across millions of square miles. The system uses trained neural networks and Bayesian methods to optimize the interaction of nodes and IoT gateways on the network.

Hence in conclusion the implications of scale of the increasingly connected world could be scary, whoever would master the management of the explosion of devices would be the winner and the ones who cannot could well be buried under the weight of the devices. A service line , AI infused Operational Support System will develop .

Email me when people comment –

An IoT enthusiast who wants to get Io to mainstream with a missionary zeal .
heading IoT and Analytics Practice for a leading Fiber Optics company . Can be reached as [email protected]

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