Optimal Path Planning for Selective Waste Collection in Smart Cities

Use of Internet of Things in the context of execution of smart city applications: a review

The Internet of Things (IoT) is rapidly becoming one of the most talked-about and essential components of any digitization process. The IoT is comprised of several key necessary components, the most important of which are sensors, communication (the internet), and user interfaces for data processing. IoTs are currently finding applications in virtually every industry, including healthcare, where they are known as the internet of medical things (IoMT), industry, where they are known as the industrial internet of things (IIoT), and interconnection between people, where they are known as the internet of everything (IoE). The challenge is to leverage the Internet of Things (IoT), technology, and data to create smarter and more sustainable cities that enhance the quality of life for residents. Therefore, in this article; we have demonstrated the use of the IoT in a variety of applications for smart communities. These applications include smart transportation, smart water management, smart garbage management, smart house illumination, smart parking, smart infrastructure, etc. This research also includes an explanation of the flow process of implementing the IoT in different applications of smart communities, as well as their characteristics and particular applications. Along with their flow illustration, the stages involved in the implementation of smart city applications and the components they consist of are also displayed here. We have also taken into consideration the instances of particular cases and their implementation utilizing IoT. Some of these cases include the automated water collection methods of smart water management systems as well as the condition of the water. Based on the findings of the research, we came to the conclusion that IoT devices play an essential role in each and every one of the smart city project implementations.

IoT based smart waste management system in aspect of COVID-19

The rapid evolution of the IoT has led to various research challenges for improving smart city applications. Owing to the characteristics and virtues of IoT services, waste management has emerged as a prominent issue in today's society. An undiscerning illegal eviction of waste, lack of waste disposal and management systems, and inept waste management policies have resulted in severe health and environmental challenges. Based on an integrative review, the proposed technique provides insight into the potential of smart cities and associated communities in assisting waste management initiatives. This study has referred to the existing waste management issues in urban areas and proposed an IoT-based smart waste management system of India in aspects of COVID-19 afflicted houses. Our system intends to improve waste management by making regular environmental sterility and making COVID situations more convenient. The proposed framework ensures a solution for efficiently handling waste generated in urban areas, focusing on the interaction among concessioners and waste generators to monitor the unfilled level of bins. This proposal offers dynamic waste collection scheduling and route optimization while achieving quality of service.

A Real-World Scenario of Citizens' Motivation and Engagement in Urban Waste Management Through a Mobile Application and Smart City Technology

Circular bioeconomy is a key socioeconomic model for advancing the United Nations Global Sustainability Goals and promoting environmental and resource sustainability. However, circular bioeconomy concepts are unknown to most people and politicians worldwide who still have a fragmented picture of sustainability. Common perception of waste needs a cultural shift from "disposable" to commodity. This can happen with effective communication, active citizens' education, and awareness and engagement in core bioeconomy experiences and activities, like urban waste management and environmental sustainability. Citizen engagement methodologies are multiple. This paper proposes the combined use of Information and Communication Technologies (ICTs), citizens' hands-on project involvement, and a direct rewarding system. Similar European examples are displayed, while our key case study is the bitter orange waste problem in the metropolitan region of Attica in Greece, where approximately 40,000 tons of bitter oranges per year remain unmanageable and unexploited, causing serious problems. The Bitter Orange Project aims to educate citizens on bioeconomy and biomass value, hopefully changing the perception of urban waste through their rewarded engagement in fruit collection to produce high added value materials. This can be a versatile platform for urban waste management projects through citizen science regardless of the type of biomass. The project aims to engage all possible local society stakeholders to multiply awareness. The target of this paper is to highlight that environmental problems related to biomass misuse are closer than the average citizen experiences, and that active involvement of society through rewarding can help raise awareness.

Multicriteria Route Planning for In-Operation Mass Transit under Urban Data

Multicriteria route planning is a crucial transportation planning issue under the field of GIS-based multicriteria decision analysis (GIS-MCDA) with broad applications. A searching algorithm is proposed to solve the multicriteria route planning problem with spatial urban information and constraints such an existing transit network in operation, certain vertices to be visited in the path, total number of vertices been visited, and length or range for the path. Evaluation of two in-operation mass-transit systems from Chicago and Tainan show that our method can retrieve solutions in a Pareto-optimal sense over comparative methods between profit under queried constraints (the expected passenger flow to be maximized, referring to the social welfare for the public) and cost for construction as well as maintenance (the cost of route to be minimized, referring to the sustainability for the government) with reasonable runtime over comparative methods.

Comparison of Optimisation Algorithms for Centralised Anaerobic Co-Digestion in a Real River Basin Case Study in Catalonia

Anaerobic digestion (AnD) is a process that allows the conversion of organic waste into a source of energy such as biogas, introducing sustainability and circular economy in waste treatment. AnD is an intricate process because of multiple parameters involved, and its complexity increases when the wastes are from different types of generators. In this case, a key point to achieve good performance is optimisation methods. Currently, many tools have been developed to optimise a single AnD plant. However, the study of a network of AnD plants and multiple waste generators, all in different locations, remains unexplored. This novel approach requires the use of optimisation methodologies with the capacity to deal with a highly complex combinatorial problem. This paper proposes and compares the use of three evolutionary algorithms: ant colony optimisation (ACO), genetic algorithm (GA) and particle swarm optimisation (PSO), which are especially suited for this type of application. The algorithms successfully solve the problem, using an objective function that includes terms related to quality and logistics. Their application to a real case study in Catalonia (Spain) shows their usefulness (ACO and GA to achieve maximum biogas production and PSO for safer operation conditions) for AnD facilities.

Machine Learning and IoT-Based Waste Management Model

A rapid rise in inhabitants across the globe has led to the inadmissible management of waste in various countries, giving rise to various health issues and environmental pollution. The waste-collecting trucks collect waste just once or twice in seven days. Due to improper waste collection practices, the waste in the dustbin is spread on the streets. Thus, to defeat this situation, an efficient solution for smart and effective waste management using machine learning (ML) and the Internet of Things (IoT) is proposed in this paper. In the proposed solution, the authors have used an Arduino UNO microcontroller, ultrasonic sensor, and moisture sensor. Using image processing, one can measure the waste index of a particular dumping ground. A hardware prototype is also developed for the proposed framework. Thus, the presented solution for the efficient management of waste accomplishes the aim of establishing clean and pollution-free cities.

IoT-Enabled Solid Waste Management in Smart Cities

The Internet of Things (IoT) paradigm plays a vital role for improving smart city applications by tracking and managing city processes in real-time. One of the most significant issues associated with smart city applications is solid waste management, which has a negative impact on our society’s health and the environment. The traditional waste management process begins with waste created by city residents and disposed of in garbage bins at the source. Municipal department trucks collect garbage and move it to recycling centers on a fixed schedule. Municipalities and waste management companies fail to keep up with outdoor containers, making it impossible to determine when to clean them or when they are full. This work proposes an IoT-enabled solid waste management system for smart cities to overcome the limitations of the traditional waste management systems. The proposed architecture consists of two types of end sensor nodes: PBLMU (Public Bin Level Monitoring Unit) and HBLMU (Home Bin Level Monitoring Unit), which are used to track bins in public and residential areas, respectively. The PBLMUs and HBLMUs measure the unfilled level of the trash bin and its location data, process it, and transmit it to a central monitoring station for storage and analysis. An intelligent Graphical User Interface (GUI) enables the waste collection authority to view and evaluate the unfilled status of each trash bin. To validate the proposed system architecture, the following significant experiments were conducted: (a) Eight trash bins were equipped with PBLMUs and connected to a LoRaWAN network and another eight trash bins were equipped with HBLMUs and connected to a Wi-Fi network. The trash bins were filled with wastes at different levels and the corresponding unfilled levels of every trash bin were monitored through the intelligent GUI. (b) An experimental setup was arranged to measure the sleep current and active current contributions of a PBLMU to estimate its average current consumption. (c) The life expectancy of a PBLMU was estimated as approximately 70 days under hypothetical conditions.

Biodegradable and non-biodegradable fraction of municipal solid waste for multifaceted applications through a closed loop integrated refinery platform: Paving a path towards circular economy

An increase in population, rapid urbanization and industrialization has accelerated the rate of municipal solid waste generation. The current disposal of solid waste is a burgeoning issue and it's in immediate need to shift the existing disposal processes to a sustainable manner. Circular economy (CE) is a conceptual model which is been used for better use of resources and minimization of waste in a closed loop approach which could be appropriate for waste management. In this context, the present review illustrates the effective use of biodegradable and non-biodegradable fraction of solid waste in a closed loop integrated refinery platforms for the recovery of bioenergy resources and for the production of value added products. The biodegradable fraction of solid waste could be treated by advanced biological processes with the simultaneous production of bioenergy such as biohydrogen, biomethane, bioelectricity, etc., and other value added products like butanol, ethanol, methanol etc. The scheme illustrates the closed loop approach, the bioenergy generated from the biodegradable fraction of solid waste could be used for the operation of internal combustion engines and the energy could be further used for processing the waste. The non-biodegradable fraction of solid waste could be used for construction and pavement processes. Overall the study emphasizes the paradigm shift of solid waste management concepts from linear economy to a circular economy following the "Zero Waste" concept. The study also explains the circular economy policies practiced for solid waste management that stimulates the economy of the country and identify the pathways to maximize the local resources. In addition the review addresses the advanced information and communication technologies to unfold the issues and challenges faced in the solid waste management. The smart governance of managing waste using the "Internet of Things" (IoT) is one of the great precursors of technological development that could lead innovations in waste management.

A Multidimensional Assessment Model Using RE-3DSG Sensors on Net ES and GVR for Sustainable and Smart Cities

With the rapid accumulation of population and industry, the urban service efficiency requirements in building sustainable and smart cities are increasingly becoming higher. However, current environmental assessment methods require large amounts of data, long assessment cycles, and tedious assessment processes; thus, they cannot quickly respond to the rapidly changing urban green space. To resolve the above problems, we present a multidimensional model for sustainable and smart cities equipped with RE–3DSG sensors to detect the real experience of residents and the three–dimensional structure of the urban green space. RE–3DSG sensors consist of two parts: The net ecosystem service (Net ES) and green volume ratio (GVR), where Net ES provides a solution consisting of runoff control, air purification, cooling, carbon sequestration, noise reduction, and recreational area establishment, while GVR assesses the spatial structure of urban built environment plant clusters. By implementing the proposed model, it is proven that it can assist users (usually decision makers in government departments) to improve the decision–making efficiency and increase the satisfaction of residents with urban green spaces, thereby achieving the goal of building a sustainable and smart city.