IoT Based Occupancy Detection System with Data Stream Processing and Artificial Neural Networks

This paper presents a model of an occupancy detection system based on artificial neural networks and data stream processing. With already available datasets, an artificial neural network was trained and the accuracy of 98.88% was achieved. Furthermore, data stream processing can be used as a part of the system for collecting and analysing data from IoT devices and their sensors.