IoT SENSOR FUSION ALGORITHM FOR REAL-TIME APPLICATIONS

Abstract

In order to increase the accuracy of scaling of multi-sensor information, this paper proposes an Improved Particle Swarm Optimization (EPSO) method on the Internet of Things (IoT) infrastructure. The IoT technologies that are necessary include an electronic sensor network, Radio Frequency Identification (RFID), an embedded system, and a group of sensors. The data aggregation is one of the significant problems, which involves the combination of data of several sensors and may be represented as a multidimensional problem by using PSO methods. In IPSO, the minimizing solution assignment themes with several dimensions for the objective cost function, mutation rules, and cross rules are taken into consideration by the proposed IPSO technique. Candidates with the best seclusion can be identified with the shortest amount of time and reduce the region that has to be searched. The proposed multi-sensor data fusion approach, which integrates IPSO, is a highly useful application, which employs the IoT systems based on the experimental outcomes.