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المؤلفSheng, Teoh Ji
المؤلفIslam, Mohammad Shahidul
المؤلفMisran, Norbahiah
المؤلفBaharuddin, Mohd Hafiz
المؤلفArshad, Haslina
المؤلفIslam, Md. Rashedul
المؤلفChowdhury, Muhammad E. H.
المؤلفRmili, Hatem
المؤلفIslam, Mohammad Tariqul
تاريخ الإتاحة2023-04-17T06:57:48Z
تاريخ النشر2020
اسم المنشورIEEE Access
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/ACCESS.2020.3016255
معرّف المصادر الموحدhttp://hdl.handle.net/10576/42007
الملخصTraditional 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. 2013 IEEE.
راعي المشروعThis work was supported in part by the Ministry of Malaysia under Grant LRGS MRUN/F2/01/2019/1/2, and in part by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia, under Grant RG-39-135-40.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعInternet of Things
LoRa
object detection
smart waste management system
TensorFlow
العنوانAn Internet of Things Based Smart Waste Management System Using LoRa and Tensorflow Deep Learning Model
النوعArticle
الصفحات148793-148811
رقم المجلد8
dc.accessType Open Access


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