How is it possible to trust an IoT ecosystem based on a test of just one or two devices within it?
As artificial intelligence (AI) becomes a core component in decision-making, the integrity of the IoT ecosystem becomes even more acute.
What are the consequences?
The gravity of this challenge varies according the IoT implementation. Quality control slippage in manufacturing from faulty temperature sensors could result in expensive losses and wasted time. But in a fully automated hospital, a connected car or critical infrastructure such as refineries, there could be waves of losses, including power blackouts and loss of life.
In predictive maintenance implementations, data about everything from a train’s brakes to aircraft engine turbines is detected by sensors and shared with a digital twin in the cloud. But what if a sensor suddenly malfunctions, that data is no longer accurate, resulting in a test not being performed correctly?
The potential consequences are incredibly serious. Which is why we are working on a solution to confirm the integrity of data, algorithms and testing within IoT ecosystems. You can learn more about this in the next instalment.
Summary
IoT sensors are generating terabytes of data daily, which can tell us about everything from our health to the quality of manufactured goods as they roll off the production line. Can those sensors, the data they generate and the decision-making ecosystems be trusted to be accurate all the time?