An Internet of Things Based Smart Waste Management System Using LoRa and Tensorflow Deep Learning Model

Teoh Ji Sheng,Haslina Arshad,Hatem Rmili,Mohd Hafiz Baharuddin,Norbahiah Misran,Md Rashedul Islam,Mohammad Tariqul Islam,Muhammad E H Chowdhury

doi:10.1109/access.2020.3016255

Abstract

Traditional waste management system operates based on daily schedule which is highly inefficient and costly. The existing recycle bin has also proved its ineffectiveness in the public as people do not recycle their waste properly. With the development of Internet of Things (IoT) and Artificial Intelligence (AI), the traditional waste management system can be replaced with smart sensors embedded into the system to perform real time monitoring and allow for better waste management. The aim of this research is to develop a smart waste management system using LoRa communication protocol and TensorFlow based deep learning model. LoRa sends the sensor data and Tensorflow performs real time object detection and classification. The bin consists of several compartments to segregate the waste including metal, plastic, paper, and general waste compartment which are controlled by the servo motors. Object detection and waste classification is done in TensorFlow framework with pre-trained object detection model. This object detection model is trained with images of waste to generate a frozen inference graph used for object detection which is done through a camera connected to the Raspberry Pi 3 Model B+ as the main processing unit. Ultrasonic sensor is embedded into each waste compartment to monitor the filling level of the waste. GPS module is integrated to monitor the location and real time of the bin. LoRa communication protocol is used to transmit data about the location, real time and filling level of the bin. RFID module is embedded for the purpose of waste management personnel identification.

Highlights

Internet of things (IoT) is a communication paradigm that envisions a future paradigm where everyday life objects will be equipped with a microcontroller and some form of communication protocol [1]
One major topic within the smart city is smart waste management. When it comes to waste management systems, the communication distance between the waste collection center and the waste collection point is a major factor in determining the system’s effectiveness. Available communication technology such as LoRa and SigFox, which operate on a low power, wide-area network (LPWAN) are able to cater to the long-distance communication needed by the waste management system while sacrificing on the rate of data transmission
We present a smart waste management system using integrated sensors, LoRa communication protocol, which has been used for the data transmission to the server, and a TensorFlow framework to train a deep learning model that performs real-time object detection and classification

Summary

Introduction

Internet of things (IoT) is a communication paradigm that envisions a future paradigm where everyday life objects will be equipped with a microcontroller and some form of communication protocol [1]. Available communication technology such as LoRa and SigFox, which operate on a low power, wide-area network (LPWAN) are able to cater to the long-distance communication needed by the waste management system while sacrificing on the rate of data transmission. Studies [4,5,6,7,8] in the field of wireless communication in IoT have been accelerating. Communication technology such as Bluetooth, Wi-Fi, and Zigbee offer better data transmission rates, but these are limited by their data transmission ranges

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