The last decade was all about the potential for the Internet of Things (IoT). We managed to connect our factories, our warehouses, and our logistics chain to the internet. We harvested massive amounts of data. However, a fundamental question remained: now that everything is connected, what are we going to do with all this data?
The industrial sphere is swiftly evolving past connected devices and towards autonomous intelligence. For quite some time now, operational teams had to deal with data overload. Yes, a smart sensor will notify you about your machine heating up, but it is still up to the human to record the alert, understand the problem, and make an appointment for repairs. The additional step results in latency, which can cost millions in the industrial environment.
The actual optimization comes from marrying AI with IoT (AIoT) and creating systems capable not only of reporting status but also of analyzing information and making decisions. It is revolutionizing several aspects of the operational process: Predictive Maintenance: Rather than using predefined maintenance schedules, predictive maintenance involves repairing equipment just before failure is imminent through vibrational and thermal analysis.Asset Tracking & Visibility: Beyond just being able to know where the asset is, predicting delays in the supply chain to reroute accordingly.Workforce Safety & Security: Environmental monitoring and access controls that can help prevent accidents and automatically restrict access to areas of potential hazard. Building out such systems requires not just well-written software code, but rather experience and expertise in the field and the ability to roll out a proper solution. This is what venture platforms such as Aperture Venture Studio are trying to achieve, by taking the problems faced in industries and building out companies around it.
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