IoT-based Smart Campus Monitoring Based on an Improved Chimp Optimization-Based Deep Belief Neural Network

Abstract

The application of IoT in monitoring the smart campus is an inevitable one to monitor the attendance of students and monitoring other activitieson the campus to protect the students and improve the education standards. Most education institutes use smart classrooms to achieve the aforementioned quality and we propose a Bluetooth-enabled IoT smart system for the positing of students with low energy utilization to automatically record the students' attendance in the cloud environment by the Received signal strength indicator (RSSI). To achieve this we propose a novel IoT-based Deep Belief Neural Network (DBN) based Improved Chimp Optimization algorithm (ICO) for positioning of the students'. An experimental study is conducted on Raspberry Pi with the deployment of Python and shows that our proposed approach provides better accuracy even with high interference signals.

Advances in real time smart monitoring of environmental parameters using IoT and sensors

“…Prediction in traditional farming is based on farmer experience, which is time-intensive and inefficient. As a result, a move from traditional farming to digital farming is required, which is doable with data-driven Internet of Things technology [ 14 , 15 ].…”