Household Waste Management System Using IoT and Machine Learning

Understanding the Barriers to Sustainable Solid Waste Management in Society 5.0 Perspective Under Uncertainties: A Hybrid Method Approach

“…(2017) assessed the cost-benefit features and energy reliability of waste-to-energy recovery utilization techniques in a capital city. Dubey et al (2020) examined a waste management collection and decomposition system towards the Internet-of-Things and machine learning in a smart society. Onoda (2020) argued for the use of S5.0 tactics to waste management and tried to make the case for an evolution in smart cities.…”

“…A society is in the 5.0 stage of its development when it is smart in terms of waste management, energy savings, and environmental conservation (Dubey et al, 2020). Still, there is no focus on infrastructure and energy consumption (A4) solutions designed to waste reduction, reuse and recycling, and energy recovery processes, resulting in big amount of disposed waste and environmental pollution (Bui et al, 2020a).…”

“…Within s5.0 perspective argues that sustainable development goals empower a new biosphere in which human beings lead wealthy and gratifying lives in harmony with social, economic, and technological progress that causes no harm to nature (UN, 2020). In this context, sustainable solid waste management (SSWM), as an integral part of human life that has a strong influence on production and consumption and long-term effects on the environment and human life, has become particularly important when reimagining society (Dubey et al, 2020). This study argues that through SSWM, S5.0 may create new value and a safe environment that make people's lives more consistent with sustainability.…”

“…For examples, Gutberlet et al (2017) indicated that unsustained waste disposal poses severe health risks, as it spreads infectious diseases and contaminates neighborhoods. Dubey et al (2020) stated that the main problem associated with a fast-growing population is the generation of biodegradable and nonbiodegradable waste that impacts the environment. Although these problems have been known for some time, local authorities have not yet been ready to deal with them, and the application of advanced operational technologies, such smart tools for big data management, and the implementation of information technology systems, is still in an early stage (Foresti et al, 2020).…”

Automatic waste segregator and monitoring system

“…The investigation at that point overlays the mediations on standards and financial motivating forces on to 'data' intercession to show signs of improvement comprehension of the effect of mediations [8]. Scientists have additionally worked upon frameworks like Household Waste Management System Using IoT and Machine Learning [9], an AWS utilizing equal resounding impedance detecting component to recognize metallic things, and capacitive sensors to recognize wet and dry waste [10], an Automatic Waste segregator utilizing a mechanical arm [11], an Automatic Waste segregator utilizing Microcontroller based stage Arduino Mega 2560 load up which is interfaced with ESP8266 12E LoLin NodeMCU V3 module, Inductive vicinity sensor, Laser module, Light Dependent Resistor (LDR), Liquid sensor module and Ultrasonic sensor [12], an AWS utilizing Arduino UNO [13], a structure that empowered the remote checking of strong burn through receptacle continuously, by means of ZigBee-PRO and GPRS, for helping strong waste administration process [14], strong waste observing and the board framework utilizing radio recurrence ID (RFID) partner with canny frameworks [15].…”