IoT and machine learning: intelligent data
In an increasingly tumultuous technological environment, new ideas are being found by creating abstractions and correlating emerging phenomena through a corporate reading: the intersection between machine learning and IoT is creating the need for new ways of organizing and understanding data, especially those coming from connected sensors and devices.
Within the Data Management research area, one of the intersections that I think is most interesting is between machine learning (ML) and Internet of Things (IoT). ML is becoming an essential player in a growing range of process areas including image recognition, natural language processing, forecasting and process optimisation.
At the same time, the IoT is creating an explosion of structured and unstructured data from a growing army of sensors capable of recording position, voices, faces, audio, temperature, feeling, health and similar data. ML is evolving to the point where it is able to draw interesting models and inferences from these real-time data streams and make these results available to analysts, as well as incorporate them directly into business processes.
The ML / IoT intersection is already well established and visible in areas such as autonomous vehicles and robotics. The IoT requirements will help define the data strategy for the coming years and will influence the integration of ML technologies into the workplace. My suggestion is to acquire sufficient knowledge of this phenomenon as soon as possible, as it will help ensure that your company can cope with the next wave of innovation in this area in the future.
Below are some links for further information:
https://spd.group/iot-digest/combination-of-iot-and-ai/
https://hbr.org/2018/10/how-a-pharma-company-applied-machine-learning-to-patient-data
