Improving Waste Management System Efficiency and Mobility with Efficient Path MANET

Many cities in India are being expanded as smart cities. In such a way, Waste management is also a big challenge in India. Researchers are continuously working on this problem in so many ways. But, the revolution of Internet of Things will play an important role as well as give way to develop an effective and efficient Smart Waste management system for the upcoming smart cities in India. The following factors are causing the problem: growth of population density and existing congested infrastructure. This paper reviews the waste management system proposed by the researchers in the past for different smart cities and then proposes an Effective and efficient smart waste management system. The proposed model developed in this paper is with respect to the Indian infrastructure and complete integration of the different stakeholders of the Waste Management System such as Smart bins, Sensors, Source areas, and Vehicles. The proposed system is efficient and effective because the system works dynamically with respect to Smart bins, collection vehicle, and routes.

The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins’ status, and exchange data with different centralized platforms. The need for such sensors is increasing; however, the proliferation of technologies comes with various challenges. For example, how can IoT and its associated data be used to enhance waste management? In smart cities, an efficient waste management system is crucial. Artificial intelligence (AI) and IoT-enabled approaches can empower cities to manage the waste collection. This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. It performs a thorough analysis based on AI-based methods and compare their corresponding results. Our solution is based on a multiple-level decision-making process in which bins’ status and coordinates are taken into account to address the routing problem. Such AI-based models can help engineers design a sustainable infrastructure system.

The study investigates the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies into Beijing's waste management system, emphasizing their effects on operational efficiency, environmental sustainability, and economic feasibility. The deployment of AI-driven route optimization and IoT-enabled real-time monitoring resulted in a 25% reduction in waste collection trips and a 30% decrease in waste overflow incidents. These advancements led to notable reductions in fuel consumption and environmental impact, while an economic analysis projected a Net Present Value (NPV) of $3.5 million over a 10-year period, affirming the financial benefits of these technologies. The findings highlight the pivotal role of AI and IoT in optimizing urban waste management practices. The study offers policy recommendations for the phased and strategic adoption of these technologies within Beijing, with the potential to enhance efficiency and contribute to the city’s sustainability objectives. Future research is advised to examine the long-term sustainability of AI-driven waste management strategies and assess the applicability of these technologies in diverse urban environments.

With massive population growth and a shift in the urban culture in smart cities, the constant generation of waste continues to create unsanitary living conditions for city dwellers. Overflowing solid waste in the garbage and the rapid generation of non-degradable solid waste produce a slew of infectious illnesses that proliferate throughout the ecosystem. Conventional solid waste management systems have proved to be increasingly harmful in densely populated areas like smart cities. Also, such systems require real-time manual monitoring of garbage, high labor costs, and constant maintenance. Monitoring waste management on a timely basis and reducing labor costs is scarcely possible, realistically, for a municipal corporation. A Smart Dustbin System (SDS) is proposed that is to be implemented in densely populated urban areas to ensure hygiene. This paper undertakes a comprehensive analysis of the application of smart dustbin systems, following an extensive literature review and a discussion of recent research that is expected to help improve waste management systems. A current SDS used in real-time is implemented with the most recent advances from deep learning, computer vision, and the Internet of Things. The smart dustbin system used in day-to-day life minimizes the overloading of bins, lowers labor costs, and saves energy and time. It also helps keep cities clean, lowering the risk of disease transmission. The primary users of the SDS are universities, malls, and high-rise buildings. The evolution of the SDS over the years with various features and technologies is well analyzed. The datasets used for Smart Waste Management and benchmark garbage image datasets are presented under AI perception. The results of the existing works are compared to highlight the potential limitations of these works.

The massive growth of population coupled with urbanization over the years has created a significant challenge of increase in waste generation. India has achieved massive developmental growth in economic and social areas but still lacks a proper waste management system. The lack of knowledge about segregation of waste into different categories and proper disposal techniques in a country like India with an accelerated population growth is a critical issue. Since trash has different disposal techniques, according to its type, segregating waste through an automated process at the point of collection will streamline the process and result in effective waste management and utilization. The mini-review article evaluates the recent literature on technologies used for municipal waste segregation and management, with the motive of providing critical information for advancement in current research. This article reviews the use of various convolutional neural network architectures for waste classification and describes in detail as to why image processing methods are preferred over sensors for segregation into respective categories. It is also important to have an efficient waste monitoring and management system for proper disposal. A comprehensive mini-review was undertaken to understand internet of things-based models proposing efficient waste handling, from the perspective of reduced costs, collection time and optimized routes. The proposed systems were compared and evaluated based on the sensors used monitoring, microcontrollers and communication protocols such as Long Range, Global System for Mobile Communication, Zigbee and Wi-Fi, which are employed for the secure and efficient data transmission.

Medical waste management (MWM) systems are considered among the most important urban systems nowadays. Cities in different countries prefer to transform their infrastructure based on sustainability guidelines and practices. Meanwhile, smart technologies such as Internet of Things (IoT) and blockchain are being recently used in different urban systems of cities that aim to transform into smart cities. MWM systems are one of the main targets of integrating such smart technologies to maximize economic and social profits and minimize environmental issues. However, the transformation of traditional MWM systems into smart MWM systems and the adoption of such technologies can be a very resource-consuming task. One of the possible tasks in this process can be the identification of factors that cause failure in the adoption of smart technologies. Therefore, this study proposes a multi-criteria evaluation model based on type-2 neutrosophic numbers (T2NNs) to identify factors contributing to failure in the adoption of IoT and blockchain in smart MWM systems in Istanbul, Turkey. Results of the case study indicate that training for different stakeholders, market acceptance, transparency, and professional personnel are the main factors that lead to failure in the adoption of smart technologies. Training for different stakeholders, market acceptance, transparency, and professional personnel factors obtained distance values of 0.494, 0.381, 0.375, and 0.278, respectively, against the best factor which is security and privacy. In order to validate the results of the proposed approach, a sensitivity analysis test is performed. Results of this study can be useful for governmental and private MWM and green companies that are planning to adopt IoT and blockchain within their waste management (WM) system.

No city can be called as smart without smart waste management system and in the very paper we have developed an integrated platform for waste management where dustbins are installed with a network of sensors and they transmit real-time data indicating the fill percentage of the bin. The purpose of this study is to develop an efficient waste management system based on Internet of things (IoT) for mobile application. We have observed traditional waste management system of India and have identified a number of issues with current systems. They are unhygienic landfills, overflowing waste bins, limited collection, lack of storage in collection vehicles, and less awareness of separated waste collection, recycling, and reuse. Therefore, this study has been proposed as a solution to cope up with the above issues. This study provides a platform for domestic users, drivers of collection vehicle, and garbage collection authority to interact with solid waste management of the country. The idea of our project was to basically alert the concerned authorities whenever the dustbin of a particular region is full and needs to be taken care of. Our objective is to cover all the dustbins of VIT University and install our smart system into those dustbins so that they could be emptied as soon as they get filled to avoid overflow of garbage and increasing the quality of the environment around the campus. We are making a prototype of the above-mentioned system.KeywordsInternet of things (IoT)Real timeUltrasonic sensorWaste management

Chapter 5 - Blockchain-based energy-efficient smart green city in IoT environments

Wireless Sensor Networks (WSNs) have many applications, such as climate monitoring systems, fire detection, smart homes, and smart cities. It is expected that WSNs will be integrated into the Internet of Things (IoT) and participate in various tasks. WSNs play an important role monitoring and reporting environment information and collecting surrounding context. In this paper we consider a WSN deployed for an application such as environment monitoring, and a mobile sink which acts as the gateway between the Internet and the WSN. Data gathering is a challenging problem in WSNs and in the IoT because the information has to be available quickly and effectively without delays and redundancies. In this paper we propose several distributed algorithms for composite event detection and reporting to a mobile sink. Once data is collected by the sink, it can be shared using the IoT infrastructure. We analyze the performance of our algorithms using WSNet simulator, which is specially designed for event-based WSNs. We measure various metrics such as average residual energy, percentage of composite events processed successfully at the sink, and the average number of hops to reach the sink.

The process of extracting and refining contaminants from drainage or wastewater so they can be recycled back into the water supply with the least amount of negative environmental impact is known as wastewater management. The current declining environmental condition necessitates the development of new strategies and tactics to guarantee safe and intelligent wastewater management systems in smart cities. The Internet of Things (IoT) and wireless sensor networks are potential technologies for treating wastewater. The comprehensive literature review develops a conceptual framework utilizing blockchain technology for an Internet of Things (IoT)- based wastewater management system in smart cities (IoT- WMS). Information is now being stored using blockchain technology to create an incentive scheme that promotes the reuse of waste water. In smart cities, tokens related to the quantity and quality of recovered wastewater are distributed to homes and businesses. However, this frequently promotes manipulating the data used to award these tokens in order to incorporate particular benefits. To determine whether there is evidence of altered IoT sensor data, anomaly detector techniques are employed. In order to facilitate the most efficient distribution of water depending on user usage at the plot holding level, this study suggests a water distribution and integrated management system based on the Internet of Things (IoT) and data analytics (DA). In addition to preventing water waste, the suggested approach would assist in gathering consumption statistics for macro-level research and town planning

Abstract: Wireless Sensor Networks (WSNs) play a key role in the Internet of Sensor Things (IoST).IoST helps collect data from environments and is used in energy trading, monitoring, smart grids, and more. Connect to the Internet and automate your surveillance system without third-party involvement. An IoST network consists of Sensor nodes that perform environmental monitoring. Wireless Sensor Networks (WSN) and the Internet of Things (I.o.T) have gained popularity in recent years as the underlying infrastructure for connected devices and sensors in a variety of sectors. The data generated by these sensors are used in smart cities, agriculture, transportation systems, healthcare systems, toll collection systems, automatic identification of road data, automatic identification of vehicle license plates, and more. It has become a proposed blockchain mechanism. The main problems and challenges of WSN are effectively reduced by using the LEACH protocol with efficient cluster head selection.

Wastewater management is a mechanism that is used to extract and refine pollutants from wastewater or drainage that can be recycled to the water supply with minimal environmental effects. New methods and techniques are required to ensure safe and smart wastewater management systems in smart cities because of the present deteriorating environmental state. Wireless sensor networks and the Internet of Things (IoT) represent promising wastewater treatment technologies. The elaborated literature survey formulates a conceptual framework with an Internet of Things (IoT)-based wastewater management system in smart cities (IoT-WMS) using blockchain technology. Blockchain technology is now being used to store information to develop an incentive model for encouraging the reuse of wastewater. Concerning the quality and quantity of recycled wastewater, tokens are issued to households/industries in smart cities. Nevertheless, this often encourages tampering with the information from which these tokens are awarded to include certain rewards. Anomaly detector algorithms are used to identify the possible IoT sensor data which has been tampered with by intruders. The model employs IoT sensors together with quality metrics to measure the amount of wastewater produced and reused. The simulation analysis shows that the proposed method achieves a high wastewater recycling rate of 96.3%, an efficiency ratio of 88.7%, a low moisture content ratio of 32.4%, an increased wastewater reuse of 90.8%, and a prediction ratio of 92.5%.

The concept of "smart cities" The Internet of Things (IoT) is a multi-layered framework that allows cities to employ urban networks to enhance economic performance, generate innovative technological solutions, and more. Smart Cities are the result of a new age in information technology and smart economy growth, based on Internet mesh networks, communication networks, transmission networks, wireless networks, and other end-to-end sensor networks. The Internet of Things (IoT) is at the heart of it. The Internet of Things incorporates sensors into common things and links them through particular protocols for sharing data and communications over the Internet. Smart detection leads, location, monitoring, and administration are all provided by this modular architecture. A smart city of excellence must overcome three main factors: instrumented, linked, and intelligent, with the help of IoT technology. At this point of IoT development, smart cities can only arise through the interconnectedness of all of these smart elements. The goal of this essay is to learn how the Internet and sensors may assist in the development of smart cities.
 The study's main goal is to figure out how the Internet of Things, or IoT, is being used in smart cities. We also want to establish the necessity for IoT systems in these smart cities, as well as the issues that they may pose to individuals and society, via the research.
 Review secondary research papers, reviews, dissertations, and online documents from the EBSCO, Scopus, and Emerald databases to analyse and comprehend the usage of IoT in smart cities and the possible problems that its implementation may provide in order to accomplish the following goals.
 Municipal requirements are getting more complicated, necessitating the adoption of new technology like the Internet of Things to ensure that all of these cities' duties are completed. Although more cities are becoming smart via the usage of IoT in a number of businesses, the study shows that this IoT system is also creating worries about the security of citizens' data.

A smart city is a vision to adopt multiple information and communication technology (ICT) solutions in the management of public affairs. Waste management problem is acute in the cities and urban areas now a days. Number of trucks roaming around, collecting waste at any time, excessive manpower requirement and inefficient monitoring are some of the difficulties we face with the conventional waste collection approach. The purpose of our work is to introduce a smart and intelligent waste management system that is able to handle the process dynamically and cost effectively. In our approach weight and volume of waste thrown in the waste bins are collected by economical sensors and then sent to cloud server using a micro-controller and GPRS. This data is used to find the waste collection schedule to maximize the collection. Location of vehicles and waste bins are used to find the shortest possible collection route for each truck which is implemented by Ant Colony Optimization(ACO) technique. The system is adaptable to dynamic changes i.e. routes blocked during waste collection process. The whole process can be monitored centrally and thus provide a high quality service to the citizens of a smart city.

Fuzzy logic based cross-layer design to improve Quality of Service in Mobile ad-hoc networks for Next-gen Cyber Physical System