AI and machine learning have been around for some time, but in recent months they have been gathering speed as the new technology to watch. As the IoT grows and develops, (and more devices become interconnected)it is producing larger sets of data, which naturally leads to more information than human minds can process.
Cue the entrance of machine learning. Its edge on the usual processing system is that rather than simply following commands, it is able to filter and learn from incoming data – learning from experience, and testing out new solutions.
Many of our everyday IoT interfaces are already using algorithms like these, particularly retail and customer-facing programs such as music providers or online stores.
Although it is already integrated into the IoT to some extent – like the IoT – users must ensure that they have concrete objectives when implementing more advanced algorithms. Many IoT devices already offer the deep learning benefits of recognising when industrial machinery is going to require maintenance, or what constitutes “regular” behaviour vs. anomalies.
The value lies in setting strict boundaries with implementation – careful labelling of data, checking and managing behaviour, and setting clear objectives to ensure your devices are sending you the most valuable and reliable data.
M2M Connectivity works with a number of leading cellular brands provide dual SIM and failover solutions as well as working on solutions to provide cellular with failover to satellite – please contact us if this is of interest.
Darren Moroney, General Manager, M2M Connectivity