M2M without M2M

By Thirumoorthy B, January 3, 2018

Machine to Machine communication, redefined.

Technology has advanced enough to match Machine behavior to Human behavior, with the help of advanced Artificial intelligence and decision making technologies. Although, the human race did not perceive machines to do more than a few complex calculations, in the beginning, machines have transformed to be more than just that. From mechanical, to computational with mere bytes of memory, machines have now advanced to make decision on their own.

In parallel, while machines evolved over time, communication technology also advanced to a great extent, enough to enable complex communications between machines simpler.

M2M or ‘Machine to Machine’ communication has evolved from mechanical connectivity through levers and gears, to wires and electricity, and now to wireless technology (Wi-Fi, Bluetooth, LTE, Low power Bluetooth, etc.).

So, why is it so important to pay attention to M2M communication in today’s world? Because, machines are now capable of taking their own decisions and these decisions could potentially induce or trigger a chain-reaction of events or actions taken by other machines.

Let’s look at some examples –

Let‘s say a machine in a car, connected with Impact sensors, senses the vehicle is going to impact some object in front of the car. The simple decision that a human would make is to apply the brakes to avoid collision. So, we would expect the machine to make the same decision and communicate with other connected devices or machines that control the break.

Let us look at another, more complicated, example where one machine (Directional sensor) needs to communicate to another machine (Guidance sensor) about an upcoming turn, but this may not be quick. Although this kind of scenario also needs M2M communication, more inputs are required to take decisions and this might not be with the same speed as the previous situation.

In such scenarios, machines can be enabled with IoT and cloud, making communication with other machine quicker.

For example, based on traffic input, in addition to directional sensor input, it can provide much better guidance inputs to the guidance sensor.

The same scenario can also be applied to those machines / IoT devices which don’t have the capability to communicate with each other directly.

Conclusively speaking, M2M (Machine to Machine communication) need not always happen with direct communication between the machines, instead, it can use cloud as an intermediate communication mechanism.

The question comes down to how quickly it can communicate. This blog is designed to provoke the thought process behind designing M2M, without M2M, using advanced, faster IoT communication mechanisms like LoRa™ and Sigfox.

Now, driverless cars are being manufactured with built-in intelligence servers at cloud level, which can guide the vehicle, remotely collecting all sensor information.

Stay tuned to the forthcoming blog, for the principles of building of a platform that can enable the kind of technology that this blog has discussed.

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Thirumoorthy B

Thirumoorthy Balasubramanian has over 20+ years experience in the software industry. He is currently working on IoT (Internet of Things), EDA, SOA style Architecture and Business Process Management (BPM) on J2EE technologies and enthusiastically researching upcoming architectural frameworks and trends in J2EE platform. He is also actively involved in research into various Social Media with specific reference to NLP (Natural Language Processing) to provide Semantic and sentiment output. He has worked extensively on Architecting and Developing imaging workflow / BPM solutions, N-tier applications, Component based application program, Intranet/Internet applications using various technologies like J2EE, ESB, .Net.

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