Edge analytics is key to preventing security breaches and protecting human safety as the IoT gathers pace, says Greenwave Systems

Data is dying and implementing analytics beyond the edge in devices is the only way to resuscitate it and ensure it prevents security breaches and potential safety threats in the workplace, as the Internet of Things (IoT) continues to gather momentum in the home and industrial sector.

This is the message being delivered by Chad Boulanger, Global VP, Business Development (IoT Analytics), at Greenwave Systems, during CeBIT 2017 which is taking place in Hannover, Germany until Friday, March 24.

Boulanger described how current systems only deploy analytics in the gateway, warning that as IoT deployments increase, data will not be provided quickly enough by this method to make it effective for mission critical applications. To be truly useful, according to Boulanger, analytics really need to be placed at the true edge, in devices.

“The situation we have at the moment is that data is being sent to a massive data lake where it is not being used,” he said. “As the IoT continues to grow, this is not going to add value. The only way to do that is to do as much as possible at the true edge of networks – within the actual devices – so that the machine knows that something is wrong right there and can take appropriate action. If the data has to travel from another part of the network, that could have a detrimental impact.” 

Boulanger went on to explain how this approach could be applied to IoT technology within any sector, from industrial IoT to the smart home, with its use in the latter protecting customers from security breaches.

“This technology can be implemented in the home to alert users at the device level that their equipment is under attack from malware or another threat, allowing the equipment to be shut down at the earliest possible moment, potentially preventing a larger scale attack,” continued Boulanger. “In industrial IoT, it is the same idea – with the implementation of edge analytics, machines can identify anomalies and shut down immediately, preventing accidents and reducing the cost of operation.” 

Boulanger concluded: “In a nutshell, the longer data has to travel, the longer an anomaly which could have a detrimental impact goes unnoticed. With edge analytics, such as those implemented in our AXON Predict module, machines and smart sensors can collect information at every step of the network, automatically detect anomalies and take immediate action right at the source of input.”