Smart Bin Research Articles

Smart Dustbins - Automatic Segregation & Efficient Solid Waste Management using IoT Solutions for Smart Cities

Abstract: Sustainability is the ability to exist continually. In the 21st century, it generally refers to the capacity for the biosphere and human civilization to coexist. There has been a spike in solid waste generation in recent times. Solid waste management is a crucial issue towards global sustainability crises. Governments across the world are taking initiatives to transform cities into smart cities. An appropriate mechanism for solid waste collection and management is vital for bringing this change. The economic value of waste is not realized unless it is appropriately managed. Internet of Things (IoT) Technologies can efficiently handle such services in smart cities. Way to sustainability is an efficient use of technology to achieve solutions to global environmental problems; solid waste management is one of the significant issues. In this paper, we are proposing an IoT based Smart dustbin monitoring system with dynamic scheduling and routing of trash collector along with moisture detection of smart dustbins. Real-time status of each smart bin is sent to the cloud. A mobile application assists the trash collector using optimal dynamic routes. Municipal corporations monitor the entire waste collection process using the proposed system. We also propose a way to automatically segregate wet and dry waste using moisture detection. Keywords: Automatic segregation, Cloud, Dynamic scheduling, Route optimization, Solid waste management, Smart cities, WetDry waste segregation.

Survey paper on Garbage Collection Management System

Abstract: Smart cities integrate multiple mobile or websolutions to build a comfortable human habitation. One of these solutions is to provide an environmentally friendly, efficient and effective garbage management system. The current garbage collection system includes routine garbage trucks doing roundsdaily or weekly, which not only doesn't cover every zone of the city but its completely inefficient use of government resources. The proposed system, where admin manage the garbage app for full online based mointoring and analyze the system. Her admin handle bins, driver, complaints from user and work report from driver. This paper proposes a cost-effective mobile or web based system for the government to utilize available resources to efficiently manage the over whelming amounts of garbage collected each day, while also providing a better solution for the inconvenience of garbage disposal for the citizens. This is done by a driver, app will provide predictive and guide routes generated through for garbage trucks. Then driver update the status of work done will be data collected. An android or web app is developed for the work force and the citizens, which primarily provides the user create complatints available smart bin.

Integrated Approach to Achieve a Sustainable Organic Waste Management System in Saudi Arabia.

Organic waste management (OWM) has always been a fundamental aspect of human populations. Approaches to OWM must be matched to the characteristics of a certain population. In this consideration, the Kingdom of Saudi Arabia (KSA) is no exception. Organizations are being aligned to focus on sustainability matters sharing significant features with universal trends, especially the integration of 3Rs (reducing waste, reusing, and recycling resources). However, the degree and nature of advancement in the direction of sustainability vary depending on the economic level of a state. High-income economies can afford to pay a higher price to integrate 3Rs technologies. Most recent endeavors have focused on achieving ‘Zero Waste’, which is costly for low-income developing countries. The expectations of OWM systems in KSA must be estimated. In this work, the situations in KSA and other countries are analyzed, and pertinent aspects are explored. Matters relating to the sustainability of OWM are conceptually assessed. This study proposes an integrated method for an organic waste management system to achieve sustainable OWM in the context of state policy and appropriate frameworks, suitable technology, institutional order, operational and monetary administration, and people consciousness and involvement. A genetic-based waste collection transportation algorithm that enhances the efficiency of waste collection truck management is presented in line with this technology. The selected routes based on the Rfs and IPv are the most efficient among those available for the examined smart bin destinations. The minimum Rfs of selected routes is less than the maximum Rfs of available routes by 2.63%. Also, the minimum IPv of selected routes is less than the maximum IPv of available routes by 27.08%. The proposed integrated approach, including the waste collection transportation algorithm, would be beneficial across a variety of country-specific layouts.

Design of Cyber-Physical Waste Management Systems Focusing on Energy Efficiency and Sustainability

Industry 4.0 tools, such as the Internet of Things, artificial intelligence, digital twinning, and cloud computing, create a technological revolution that accelerates efforts to optimize the efficiency of cyber-physical operations and services. The waste management system requires a critical share of city logistics optimization, especially when using cyber-physical systems. Modern tools reduce the required municipal waste handling, such as loading and unloading, transportation, and warehousing, which leads to an increase in efficiency and flexibility, saving energy and time, and protecting the environment. In this paper, we present a cyber-physical waste management system solution by providing a cyber-physical model design and description, mathematical modeling, and two cases to investigate the impact on energy consumption and emissions. After an introduction and literature review, we describe the design of the cyber-physical model and tackle the first echelon. The designed system incorporates the IoT, smart bins with multi-percentage sensors, data and information analysis, vehicles’ actual routes, energy and emissions optimization, multi-echelon systems, time windows, and flexibility. Mathematical modeling equations for the optimized total energy consumption are presented. Thirty and twenty smart bins located in VIII District in Budapest are detailed as two case studies, where solutions for the optimized real routes and energy consumption are found using three metaheuristic algorithms: genetic, particle swarm, and simulated annealing optimization algorithms. The accrued emissions of CO, NMHC, CH4, NOx, and PM for the optimized solutions are calculated. Finally, the results are compared with a random traditional solution to measure the effectiveness.

Industrial Internet of things-based solar photo voltaic cell waste management in next generation industries.

Nowadays, modern industries generate their energy by using renewable solar. The rapid increase in photovoltaic (PV) module installations provides a better energy conversion, but their life cycle is a major concern. This research paper focuses on the recycling process for solar PV modules using the Internet of Things in industries. The smart bin with the Internet of Things (IoT) utilizes a machine learning approach to collect solar waste. The proposed smart bin uses k-Nearest Neighbor's algorithm (k-NN) and Long Short-Term Memory (LSTM), a network-based learning algorithm. These algorithms are useful in updating the level of the bin via alert messages. It also helps in identifying the type of waste material. The k-NN algorithm provides 83% accuracy in predicting the bin level in a real-time testing environment. The smart dust bin classifies the waste materials, and notifies its level to the collection center through the IoT platform when the level reaches a prescribed threshold, the signal corresponding to the level is passed to the common waste collection unit. IoT is connected to Cloud Server. It helps to predict the level of the smart bin. Delay is introduced in the order of 3-8s while the alert message is sent to the common waste collection unit. The system monitors the smart bin levels and sends the notifications to alert and initiate the collection unit. Real-time mobile app monitors the bin's level and location. The cloud IoT analytics analyze the solar e-waste in a different locations in industries.The proposed system works better and provides accurate results by using machine learning approach.

Smart waste management system for decision makers by using smart bins - a case study for an Australian municipality

ABSTRACT Waste Management has become a challenging topic for fast-growing areas in many countries. The situation became worse when more and more countries have banned the import of different types of wastes. In this paper, we showcase a real-life example of an intelligent way of managing waste using Smart Bins over the Internet of Things and an integration with a dashboard system for decision-makers. We examined if there is any correlation between the smart bins’ fullness and the date or month.

Smart Garbage Bin Based on AIoT

Waste management and monitoring is a major concern in the context of the environment, and has a significant impact on human health. The concept of the Artificial Intelligence of Things (AIoT) can help people in everyday tasks in life. This study proposes a smart trash bin to help solve the problem of waste management and monitoring. Traditional methods of garbage disposal require human labor, and pose a hazard to the worker. The proposed smart garbage bin can move itself by using ultrasonic sensors and a web camera, which serves as its “eyes.” Because the smart garbage bin is designed for indoor use and mobility, we use a Bluetooth beacon for location tracking, whereby the bin transmits a constant signal that the other devices in the environment can detect. A smart garbage bin was developed in this study to be used in the E315 research room in the Electrical Engineering Department of the National Chin-Yi University of Technology. An Android application was also developed to help users monitor waste in the smart bin.

Domestic Waste Management with Io-enabled Applications: A Case Study of the Al Rayyan, Qatar Region

Domestic waste management is considered as a critical practice that must be followed from the time waste is generated until the time it is disposed of. The integration of smart bins in the waste management process increases the demands on the waste collection strategy. This study looks at how the internet of things (IoT) can be used to improve waste collection systems. It contrasts a standard periodic review technique with an IoT-enabled strategy in which we assume garbage bins are equipped with smart sensors that provide continuous monitoring of the bin's status. A simulation model is developed that is based on two modules: the waste generation and the waste management. The Al Rayyan, Qatar region's partial data is simulated using various parameter values and scenarios. The simulation is validated by taking economic, environmental, and citizen satisfaction performance measures into account. The results of the experiments revealed that each collection method performed well in a specific situation. In comparison to the periodic review waste collection method, the truck travels fewer miles while meeting economic, environmental, and public satisfaction goals in the IoT-oriented method.

Medical waste management in healthcare institutions

Studies over the past decade have shown that medical waste generated has increased significantly and will continue to increase with the pandemic. To identify solutions to solve this global issue, the assignment focuses on defining the existing waste management practices followed in developing countries and highlights specific challenges faced. The purpose of this assignment is to identify ways where healthcare organizations can improve the overall medical waste management (MWM) process and create awareness among co-workers. The assignment is divided into three main components where critical analysis of primary research, policy for waste management and use of IT/IS tools were analyzed. Three articles analyzed in this assignment were published in high impact journals/international reports between 2014-2018. Findings from the primary research were obtained using a Likert-scale questionnaire from 156 healthcare institutions, the results indicated that MWM practices followed in healthcare institutions are impacted by three factors, awareness of staff, technological availability and attitudes of top-board management. The three factors had a p-value of 0.00 in the correlation analysis carried out indicating a highly significant relationship between them. Integrated sustainable waste management model following the GWMO (Global Waste Management Outlook) framework was identified to be most adaptable method. The advantage of this model is such that it can be remodeled based on the country’s requirement with the help of digital tools and country-level indicators. The use of IT/IS tools were critically analyzed in the last article with use of GIS integrated real-time waste management system being identified as the most feasible option, where using online tracking systems and smart bins the type of waste and quantities produced can be measured and provide real time updates to local authorities to ensure safe waste management practices are followed. Recommendations from the assignment identifies that countries needs to conduct a preliminary analysis of types of medical waste being generated in healthcare institutions to provide a better understanding of types of hazardous waste exposed to the environment. Additionally, frequent training workshops needs to be conducted to ensure the management and staff understand the importance of MWM.

Design and Development of IoT based Garbage Monitoring and Management System

Daily garbage production causes increasing in garbage management and cleansing cost which required an approach for better monitoring and management system to be applied. Currently, demand of IoT keep increasing as a part of Industrial Revolution 4.0 (IR4.0). Eventually, this IoT based Garbage Monitoring and Management System has been developed. For hygiene, self-opening dustbin lid is applied and IoT technology is used to integrate better garbage monitoring and management into an innovative and effective system. The development of this smart bin uses a pair of infrared sensors and an ultrasonic, push notifications were developed in Blynk application, and user-friendly infographic data is designed on webpage for monitoring and garbage management purposes. The smart dustbin notifies the user when the garbage level exceeds 80%. The dustbin sends a push notification to the user’s phone to alert the user to take actions needed before the bin exceed the limit.

THE SMART WASTE MANAGEMENT SYSTEM OF SOLID WASTE MANAGEMENT IN UNIVERSITY CAMPUS

It has been a challenge for Malaysia to handle solid waste management for more than a decade. The increase in population size has led to an increase in the waste amount contributed by Malaysians. Due to that, proper solid waste management is essential in protecting the environment. There are many ways to execute solid waste management but developing countries may find it challenging to find the best way to dispose of waste efficiently. The same phenomenon seems to happen on university campuses as well. This article aims to propose a smart waste management system for university campuses. Most of the related work concentrates on detecting bin levels, despite making it a full-fledged system that comprises several modules regardless of web or mobile platform. A prototype of a smart bin is proposed, and this paper discusses its architecture and functionality. A web-based user application is also proposed in this article. With these components, the system enables the user to obtain information on the bins around them and can help the management to manage solid waste more efficiently. With the help of the Internet of Things and Cloud services, the system can achieve a greener and more sustainable campus environment. The proposed system will also be enhanced further to increase the awareness among the university students to move forward to a greener campus.

Smart Bin: A Much-Needed Revolution in the Garbage Management System

Abstract: A clean setting is what they want of this era. Within the name of industrialization and development, a man started destroying mother earth. As a result, garbage pickup has crossed the amount of selling. Garbage management could be a serious issue that has been increasing day- by- day. So, managing it became the priority of today’s world. As the man had understood the importance of mother earth moreover as nature. Some pretty solutions had been implying by IoT. Smart cities, smart garbage management systems, smart bins are the different ways to manage waste. This paper includes two better ways of handling waste. The robotic arm and Eddy Current separator concept are used as they are the latest of all. To make the garbage management system more effective these concepts should come in front. Human intervention will be excluded. Making it one of the powerful solutions. Saving our mother earth is the responsibility of every citizen. Though people had understood the importance of our nature and taking the necessary steps to save it. Keywords: Garbage Management System, Smart Bin, Robotic Arm, Eddy Current Separator, Municipal Solid Waste.

Digital Garbage System using Arduino NANO

Abstract: Garbage bins or dust bins are those that are put in public places in cities and are currently overflowing due to an increase in waste every day. It harms people's health by spreading deadly infections. To avoid this, smart bins will be designed with sensors such as an infrared sensor, a weight sensor, a photoelectric sensor, and radio frequency identification (RFID) card reader. If someone throws trash into the smart bins, a photoelectric sensor will identify the clear representation objects, and a weight sensor will be positioned beneath the smart bin to calculate the percentage of garbage present it will forward the information to the authorities in charge of that specific location. As a result, the relevant authorities can get messages until the bin is squished, and each bin is assigned a unique ID, which will appear on the screen of the respected officer, allowing them to take fast action. If a person is within two meters radius of the bin that contains an RFID CARD READER, the RFID reader will read all of that person's information and send a message to him about what they placed into the bin, as well as an appreciation message for using the bin. Keywords: Arduino NANO, GSM Module, Smart Dustbin, IoT, Arduino Uno.

A review on modern and smart technologies for efficient waste disposal and management

In the current scenario, the word waste management holds much importance in every individual's life. Pollution and the generation of vast waste quantities with no proper waste management process have become one of humanity's biggest threats. This review article provides a complete review of the innovative technologies currently employed to handle and dispose of the waste successfully. This work aims to include the different solid, liquid, gaseous, and radioactive waste management processes. The novel and improved plasma gasification concepts, transmutation, incineration, bio-refineries, microbial fuel cells (MFC) have been thoroughly explained. In addition, some new techniques like Mr. Trash Wheel and the Smart bin approach provide much hope of adequately managing waste. The work's novelty lies in adopting several successful methods of various countries for waste disposal and management. To incorporate or improve India'sIndia's same techniques and processes, we have to tackle the ever-increasing waste disposal problems and find economic and eco-friendly ways of waste management.

Real-time localisation system for GPS-denied open areas using smart street furniture

Wifi-based localisation systems have gained significant interest with many researchers proposing different localisation techniques using publicly available datasets. However, these datasets are limited because they only contain Wifi fingerprints collected and labelled by users, and they are restricted to indoor locations.We have generated the first Wifi-based localisation datasets for a GPS-denied open area. We selected a busy open area at Murdoch University to generate the datasets using so-called “smart bins”, which are rubbish bins that we enabled to work as access points. The data gathered consists of two different datasets. In the first, four users generated labelled WiFi fingerprints for all available Reference Points using four different smartphones. The second dataset includes 2450865 auto-generated rows received from more than 1000 devices.We have developed a light-weight algorithm to label the second dataset from the first and we proposed a localisation approach that converts the second dataset from asynchronous format to synchronous, applies feature engineering and a deep learning classifier. Finally, we have demonstrated via simulations that by using this approach we achieve higher prediction accuracy, with up to 19% average improvement, compared with using only the fingerprint dataset.

Design of Smart Bin for Waste Management

Design of Smart Bin for Waste Management

A Collaborative Application for Assisting the Management of Household Plastic Waste through Smart Bins: A Case of Study in the Philippines.

The management and collection of household waste often represents a demanding task for elderly or impaired people. In particular, the increasing generation of plastic waste at home may pose a problem for these groups, as this type of waste accumulates very rapidly and occupies a considerable amount of space. This paper proposes a collaborative infrastructure to monitor household plastic waste. It consists of simple smart bins using a weight scale and a smart application that forecasts the amount of plastic generated for each bin at different time horizons out of the data provided by the smart bins. The application generates optimal routes for the waste-pickers collaborating in the system through a route-planning algorithm. This algorithm takes into account the predicted amount of plastic of each bin and the waste-picker’s location and means of transport. This proposal has been evaluated by means of a simulated scenario in Quezon City, Philippines, where severe problems with plastic waste have been identified. A set of 176 experiments have been performed to collect data that allow representing different user behaviors when generating plastic waste. The results show that our proposal enables waste-pickers to collect more than the 80% of the household plastic-waste bins before they are completely full.

Perception Study on IOT Based Waste Management System

The concern over proper waste management has been there for decades, but the increasing population and immense urbanization have made the masses accept it as a serious issue. The unhygienic surrounding originating due to over spillage of dustbins is degrading the environment, which gives birth to numerous health issues. With the conceptualization of the internet of things (IoT) over the last decade and enhancement in internet infrastructure, these have become an integral part of the human lifestyle. The upcoming 5G technology will revolution the way of communication between static and mobile IoT devices. This will enhance community access to IoT devices. Thus, this has led to the concept of a “Smart Waste Management System,” an embedded system consisting of modern sensors, microcontrollers, memory, communication devices, etc. enabling real-time Monitoring for smart bins leading to reduce garbage collection cost and fuel consumption. This paper discusses a variety of IoT device’s implementation and societal perception on challenges and opportunities concerning India. Descriptive research was carried out upon data collected, and statistical analysis was done to study the differences concerning demographic, psychographic, behavioral, and geographic segmentation. The research will also provide insight to companies as well as to the waste management authorities into the commercialization of the “Smart Waste Management System”.

Smart Electronic Bin Using IoT

The amount of garbage that humans generate is rapidly increasing, and it will be impossible to control without radical adjustments. Such increases will have a significant impact on waste management firms, since they would be required to supply resources for garbage collection with little or no money. The goal of this project is to create a smart real-time waste controller system using the conceptual model of a smart electronic bin, which can be built by maximizing resource efficiency and optimizing the resources. This smart garbage bin prototype can automatically open the lid when it recognizes persons who wish to dispose of their trash. Even if people wish to dispose of their trash, if the waste bin is full, the lid will not open. It can also segregate plastic and non-plastic wastes. This smart bin is equipped with additional components such as GPS and GSM, for showing the location and to send alert messages. It can also detect the amount of trash in the garbage bin. The percentage-level of waste inside the bin is determined using an ultrasonic sensor. This data is delivered to a cloud-based monitoring and analytics IoT platform

E-Waste Bin for Disinfection and Waste Management of Masks

The corona virus pandemic has shook the entire world and the major precautionary measure for this is to wear masks. The demand and supply of these masks has increased drastically, with majority of population using surgical three, two or one ply masks which is generally thrown after its use. The first thing that is in contact with the masks is nose and mouth of the person wearing it. These masks are becoming carrier of the virus due to improper disposal methods used. Until the masks are not disinfected they are not safe to be disposed in dumping yards. There are many rag pickers who enter the dumping yards to collect recyclable wastes or the person who collects the garbage from individual homes become people of high risk to the exposure of this virus. The proposed work presents a novel approach to eliminate this problem by employing a smart electronic bin which has a disinfection section which will disinfect the masks using UV-C lights and then it will be dumped into the bin installed just below the unit. This bin has a level sensor which will monitor the level of waste in the bin and whenever it gets full, it will notify the concerned authority on his mobile using Blynk app. The Blynk app interface is designed to present the status of level of waste in the bin.