WHAT IS MACHINE-TO-MACHINE TECHNOLOGY?

In supply chain management, M2M is primarily EDI (Electronic Data Interchange) or middleware to connect to systems and transfer messages.

The supply chain industry in general are a bunch of laggards when it comes to the adoption and use of technology, so there are only a few leading companies who are early adopters and fleets covered with GPS (Global Positioning System) transponders or who have adopted EDI standards across businesses through machine-to-machine communication.

The big move in the industry is about the use of internet standards as oppose to numerous bespoke systems of electronic communication. For example, there are 185 different GPS standards in the telematics marketplace which is clearly unsustainable. They will require, either to end up using one generic standard or alternatively a central translation hub which will be able to process any format of GPS message.

So, M2M is quite limited within the supply chain industry and it is principally used in track and trace of vehicle and goods movements. Real-time vehicle management and engine management using either GPS is more widely utilized and has great potential to increase both the reliability and productivity of vehicles.

WHAT ROLE DOES BIG DATA AND DATA SECURITY PLAY IN M2M TECHNOLOGY?

Data security is absolutely vital for companies invariably dealing with mission critical commercial data. Cyber-attacks have become an ever-increasing threat to businesses. For example, one of the UK’s largest telecom companies who had more than 4 million customers was affected by a data breach where customer’s personal information, bank details, passwords etc. was at stake. The company was not only under pressure, but their reputation was seriously damaged.

So, the ability to provide maximum levels of security is absolutely vital and more data that is processed and connected via supply chain data using technologies like GPS, GSM (Global System for Mobile Communications) or other M2M type of communications the larger the “opportunity” becomes. The biggest challenge is how companies are going to use this large amount of data.

Big data really becomes relevant in the supply chain industry as volume of data increases and currently, big data is much more strategic in a business than tactical.

Big data is still over-hyped in the logistics industry and certainly there are no tactical applications, but most of it is strategic looking at particular performance on traffic lanes etc. So, it is not delivering great benefits to the industry yet.

ARE THERE ANY MARKET BARRIERS THAT MUST BE ADDRESSED TO REALIZE THE FULL SCALABILITY OF M2M TECHNOLOGIES?

There are no technology barriers, but there are lots of skepticism amongst the potential users of machine-to-machine. The supply chain industry, in particular is very slow in adopting to the technology, so there are more number of followers as opposed to early adopters.

The principle barrier is people, people’s attitudes to the new technology. There is very high reliance on manual processing within the supply chain industry and that is something many companies go through.

WHAT KIND OF LEGAL FRAMEWORK IS REQUIRED?

Data security is of utmost importance because of the nature of data companies deal with such as orders, pricing and product information etc. Clearly, this data needs to be widely shared to get maximum benefit. Security is provided by a neutral trusted third party (TTP) who manages the data and protects it from theft, loss and unauthorized access.

HOW WILL MACHINE-TO-MACHINE TECHNOLOGY AID IN REAL-TIME FREIGHT MATCHING? CAN YOU GIVE US SOME EXAMPLES?

One of the UK based companies, TGMatrix is working on a project to transform the transportation industry through automated matching of supply and demand. It matches supply and demand across all transport modes (rail, road, short sea, coastal shipping and inland waterways) in real-time using an algorithmic driven matching engine.

It is a 100 percent machine-to-machine and there is no manual intervention. It automates the process through a combination of master data and transactional data fed to the platform via EDI directly from shipper’s ERP (Enterprise Resource Planning) or TMS (Transport Management) systems.

M2M technology is already in-use in the industry for engine management to drive efficiency and reduce breakdowns. For example, using this technology, one can predict when something is going to break on a vehicle and this helps to plan preventative maintenance. Traffic jams are often caused by vehicles breaking down which probably could have been predicted if such a system is installed in vehicles to monitor the performance of key components in real-time.

Optimal real-time routing will reduce journey times, lower carbon emissions and reduce traffic congestion. Using multi-agent technology, it is possible to achieve a very sophisticated optimization in real-time linked to very high volume processing units. The use of Graphic Processing Units (GPU) at many hundreds of times faster than conventional CPU’s enables the automation of the highly complex task of matching freight and the assets to move it which can involve hundreds of variables).

In the near future, M2M technology will be used in real-time re-routing of vehicles around incidents, accommodating changes in weather patterns and ensuring efficient delivery times, lower carbon emissions and reduced congestion.

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