Smart Waste Management System Research Articles

Enhanced Route Selection (ERS) algorithm for IoT enabled smart waste management system

Abstract Internet of things (IoT) is a promising technology that provides emerging and potential solutions for the modernization of the traditional systems. It enables the notable enhancement in smart home, smart industries, smart cities, smart environment, etc. Particularly smart waste management system plays a vital role in modernization of tradition waste management system in the big cities. Data transmission delay is one of the biggest challenges in wireless sensor networks. To overcome this challenge, we proposed efficient routing technique for smart waste management system using Enhanced Route Selection (ERS) algorithm which will overcome the data communication delay by considering one of the vital QoS parameter end-to-end delay. The proposed method considers the length of the routing path, link reliability, hop count in the path and energy availability. The proposed architecture is simulated in NS3 Tool and it outperforms than existing methods in the related field with respect to the optimization of End-to-Delay, average remaining energy and average energy consumption.

SMART Computational Solutions for the Optimization of Selected Technology Processes as an Innovation and Progress in Improving Energy Efficiency of Smart Cities—A Case Study

The paper presents advanced computational solutions for selected sectors in the context of the optimization of technology processes as an innovation and progress in improving energy efficiency of smart cities. The main emphasis was placed on the sectors of critical urban infrastructure, including in particular the use of algorithmic models based on artificial intelligence implemented in supervisory control systems (SCADA-type, including Virtual SCADA) of technological processes involving the sewage treatment systems (including in particular wastewater treatment systems) and waste management systems. The novelty of the presented solution involves the use of predictive diagnostic tools, based on multi-threaded polymorphic models supporting decision making processes during the control of a complex technological process and objects of distributed network systems (smart water grid, smart sewage system, smart waste management system) and solving problems of optimal control for smart dynamic objects with logical representation of knowledge about the process, the control object and the control itself, for which the learning process consists of successive validation and updating of knowledge and the use of the results of this updating to make control decisions. The advantage of the proposed solution in relation to the existing ones lies in the use of advanced models of predictive diagnostics, validation and reconstruction of data, implemented in functional tools, allowing the stabilization of the work of technological objects through the use of FTC technology (fault tolerant control) and soft sensors, predictive measurement path diagnostics (sensors, transducers), validation and reconstruction of measurement data from sensors in the measuring paths in real time. The dedicated tools (Intelligent Real Time Diagnostic System − iRTDS) built into the system of a hierarchical, multi-threaded control optimizing system of SCADA system allow to obtain advanced diagnostics of technological processes in real time using HPC technology. In effect of the application of the proprietary iRTDS tool, we obtain a significant rise of energy efficiency of technological processes in key sectors of the economy, which in global terms, e.g., urban agglomeration, increases the economic efficiency.

Industry 4.0 based sustainable circular economy approach for smart waste management system to achieve sustainable development goals: A case study of Indonesia

Indonesia is facing a number of independently managed challenges related to the collection, transportation, processing (composting, recycling), and landfill dependence on waste management. An intervention is needed to bring stakeholders together to solve these waste challenges. The objectives of this study are to investigate the fundamental issues and opportunities and to develop a sustainable and smart country-wide waste management system using industry 4.0 technologies. The system should provide a multi-dimensional approach, determine the maturity level of the waste management system in a technical method, and pursue the goal of designing a new strategy to minimise waste management problems. A comprehensive systematic literature review, intensive focus group discussions, and direct observation in Indonesian cities were approaches used to develop waste management business processes and their system design. Waste business processes consist of mixed-collecting, sorting, transporting, varied-treatment, and chained-disposal. The design of the proposed waste management system presents circular economy processes that can separate municipal waste, identify waste characteristics, and determine sustainable waste treatment technologies through the use of Internet of Thing (IoT) as the integrator. This study contributes to the sustainable development goals (SDG’s) such as Good health, and wellbeing (SDG 3); Clean water and sanitation (SDG 6); Decent Work and Economic Growth (SDG 8); Responsible Consumption and Production (SDG 12) and Climate Action (SDG 13). The study proposes a new design of smart and sustainable waste management which could achieve satisfactory economic, social, and environmental waste management performances.

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

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.

Smart Solid Waste Management System Using IOT

The smart city consists not only the suffocated facilities but also it should consist of a smart solid waste management system. The huge generation of solid waste and shortage of land for dumping results in search of best schemes. Collection, transportation, and disposal of solid waste is a huge concern and also a very challenging task. Proper tools like IoT should be employed to integrate these works smoothly and efficiently. IoT consists of sensors which help in indicating the waste levels and collection routes to the server, from which the waste was collected in a quick and efficient manner. IoT contributes in all stages of waste management, which results in saving of time and money.

Blockchain-based Smart Waste Management System

Blockchain generation and the Internet of Things are two of the most famous technology these days. IoT is an interconnection of devices which have the usefulness to detect, degree, a strategy the country of natural markers just as themselves and incite dependent on the enter outfitted. It can help make astute arrangements which could enhance the best of ways of life of individuals. In like manner, blockchain is dispensed database structures that guarantee an extreme dimension of wellbeing and accessibility of actualities with least exchange overhead. In this proposal, we endeavor to convey together that two innovation to grow a Smart Waste Management System (SWMS). The SWMS is weight-based for example Clients need to pay for the utilization of administrations as indicated by the measure of waste they produce. Installments are made the use of a custom digital currency controlled by utilizing Smart Contracts and the total SWMS can be supported with the guide of a DAO through a totally computerized, observably secure strategy. Blockchain can help bring down the infiltration and supplier esteem which might be particularly valuable to developing countries in which governments are not exceptionally inventive. This paper tries to set up an evidence of concept thru size of performance and evaluation of the applicability of this type of device.

Optimal Management of Solid Waste in Smart Cities using Internet of Things

Smart cities are benefiting from Internet of Things (IoT) in optimizing their services. Smart waste management systems can provide substantial savings in time, monetary cost, trip length and utilization of vehicles. In this paper, we use the IoT technology to determine the schedule and pathways of waste collection trucks. We discuss our previous work on single truck routing algorithm and develop and simulate two-step heuristic algorithm multiple trucks routing algorithm (MITRA) to discover the ideal route for the management waste fleet, using smart dumpsters and agent-based models. The smart dumpsters are equipped with the sensors that measure levels of waste and a controller to send updates to the central management system using wireless network. Our target is to improve the waste collection process by reducing the congestion on the road, the service time spent and the overall trip length. We developed the MITRA algorithm applying the timing constraint on capacitated vehicle routing problem. MITRA divides the metropolitan area into a set of sectors each containing a number of dumpsters. We guide the routing in waste collection by selecting the order of sectors to be served then then apply genetic algorithm to compute the optimal route to serve the full dumpsters in the sector.

Resource Provisioning and Scheduling Techniques of IoT Based Applications in Fog Computing

Internet of Things (IoT) has emerged as a computing paradigm to develop smart applications such e-health care systems, smart city, smart waste management systems, etc. It contains a large number of different devices and heterogeneous networks, which make it difficult to provide secure and fast response to the end user. To provide the faster response services, there is a need to use the concept of Fog computing Recently, the use of fog computing is a rapidly increasing in many industries for the development of applications such as manufacturing, e-health, oil and gas, As more and more users have started to store/process their real-time data in Fog-based Cloud environments, resource provisioning and scheduling of IoT based applications becomes a key element of consideration for efficient execution of these applications. This article will help to select the most suitable technique for processing smart IoT based applications in Fog computing environments.

An Automated Machine Learning Approach for Smart Waste Management Systems

This paper presents the use of automated machine learning for solving a practical problem of a real-life Smart Waste Management system. In particular, the focus of the paper is on the problem of detection (i.e., binary classification) of emptying of a recycling container using sensor measurements. Numerous data-driven methods for solving the problem are investigated in a realistic setting where most of the events are not actual emptying. The investigated methods include the existing manually engineered model and its modification as well as conventional machines learning algorithms. The use of machine learning allows improving the classification accuracy and recall of the existing manually engineered model from $86.8\%$ and $47.9\%$ to $99.1\%$ and $98.2\%$ , respectively, when using the best performing solution. This solution uses a Random Forest classifier on a set of features based on the filling level at different given time spans. Finally, compared to the baseline existing manually engineered model, the best performing solution also improves the quality of forecasts for emptying time of recycling containers.

Custom Block Chain Based Cyber Physical System for Solid Waste Management

The aim of this paper is to develop an intelligent cyber-physical system for the waste management in a locality which will not only keep records of the use of the trash bins in the but also ensure they have an additional blockchain based verification system which will ensure the proper working even in the presence of an adversary. The proposed system is an ensemble of the database server, blockchain server, embedded system based clients and an android app. This is inspired by the recent global trend in smartphone popularity which has piqued interest in the above mentioned division. The advent of smartphone popularity helps us to create an ideal system for a plethora of reasons such as processing capability and native storage etc. Furthermore, blockchain technology, introduced by Satoshi Nakamoto in 2009 ensures decentralization and security of transactions due to its use of cryptographic hash functions and public key cryptographic system. To further excite the situation, India recently revised its solid waste management policy in 2016 after 16 long years. All of the above factors together pointed to creation of a smart waste management system to prevent further exacerbation of India’s existing waste management crisis.

Efficient smart garbage management system using IOT technique

The Proposed Smart Waste Management System is to manage the waste with the help of smart sensors along with data fill-level indication, the garbage existence all over dustbin, containers and garbage bins foul smelling conditions will be sent as an alert to the registered / specified workers as an message. An accredited mobile number that are working in Waste Management Centres gathers fill-level. The remaining of multiple containers information transmitted where it placed all over the marginal location. Gathered data from the above process, utilised for gathering the garbage in a systematic plan and a route-map. Used communication devices in the implemented project transmitted the data from garbage bin to the authorised persons. An eight bit microcontroller i.e Atmega328P regulated the total functionality of this system. This narration demonstrates an effective design of IoT gateway which is utilised for offering the “smart waste management system” framework.

Hadoop Oriented Smart Cities Architecture.

A smart city implies a consistent use of technology for the benefit of the community. As the city develops over time, components and subsystems such as smart grids, smart water management, smart traffic and transportation systems, smart waste management systems, smart security systems, or e-governance are added. These components ingest and generate a multitude of structured, semi-structured or unstructured data that may be processed using a variety of algorithms in batches, micro batches or in real-time. The ICT architecture must be able to handle the increased storage and processing needs. When vertical scaling is no longer a viable solution, Hadoop can offer efficient linear horizontal scaling, solving storage, processing, and data analyses problems in many ways. This enables architects and developers to choose a stack according to their needs and skill-levels. In this paper, we propose a Hadoop-based architectural stack that can provide the ICT backbone for efficiently managing a smart city. On the one hand, Hadoop, together with Spark and the plethora of NoSQL databases and accompanying Apache projects, is a mature ecosystem. This is one of the reasons why it is an attractive option for a Smart City architecture. On the other hand, it is also very dynamic; things can change very quickly, and many new frameworks, products and options continue to emerge as others decline. To construct an optimized, modern architecture, we discuss and compare various products and engines based on a process that takes into consideration how the products perform and scale, as well as the reusability of the code, innovations, features, and support and interest in online communities.

Implementation of spatial smart waste management system in malaysia

One of the challenges to innovate and create an IoT -enabled solution is in monitoring and management of the environment. Waste collection utilizing the Internet of Things (IoT) with the technology of smart wireless sensors will able to gather fill-level data from waste containers hence providing a waste monitoring solution that brings up savings in waste collection costs. One of the challenges to the local authority is how to monitor the works of contractor effective and efficiently in waste management. This paper will propose to the local authority the implementation of smart waste management in Malaysia to improve the city management and to provide better services to the public towards smart city applications.

A Decision Support Application in Tracking Construction Waste Using Rule-based Reasoning and RFID Technology

AbstractProtection of the environment is currently a high profile concern and this is resulting in more effective recycling and reuse of materials. This paper outlines a research project for developing and using a ‘Technology Hub’ framework combining Computational Intelligence – Rule-based Reasoning technology and Radio Frequency Identification (RFID) technology in the waste management sector. This framework has been developed using a case study based on a local waste recycling company. The project aims to help recycling companies in tracking, scheduling and intelligently handling incidents of waste movement in order to prevent fly-tipping and improve their management efficiency. Finally, the development procedure for a smart plasterboard waste management system is outlined, which includes a detailed discussion concerning the Rule-based Reasoning system design. This application provides a solution that a company can use to monitor the fleet/waste status and also generate decision support automatically in ...