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Waste can be converted to a high-value asset if treated properly with smart solutions. The purpose of this research is to identify critical barriers hindering smart waste management (SWM) implementation in developing economies using comparative analysis and a mixed-method approach. The objective of this work is to provide exhaustive insight including the smart cities projects to discuss the deferring parameters toward IoT-enabled waste management systems.

To accomplish the objective, the present study followed mixed-method approach consisting of two phases: In the first qualitative phase, barriers in the adoption of IoT (Internet of Things) for SWM were identified using extensive literature review and discussion with selected experts. In the second phase, the quantitative analysis using the Fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) method was performed on the selected barriers. The fuzzy DEMATEL methodology helps in prioritizing the most significant causal barrier by separating them into the cause-effect group. The comparative analysis was used to understand two different perceptions. To provide more detailed insight on the problems faced while implementing SWM in developing economies.

The results disclose that “Lack of government strict regulatory policies,” “Lack of proper financial planning” and “Lack of benchmarking processes” are the most critical causal barriers toward IoT-enabled SWM implementation that are hindering the vision of efficient and effective waste management system. Also, “Difficulty in implementing innovative technologies” and “Absence of Dynamic Scheduling and Routing” fall under the potential causal category. The effect barriers include “Lack of awareness among the community,” “Lack of source segregation and recycling commitment” and “Lack of service provider” as concluded in results considering the comparative analysis. The results can aid the policy-makers and stakeholders to identify the significant barriers toward a sustainable circular economy and mitigate them when implementing IoT-enable waste practices. Also, it assists to proactively build programs, policies, campaigns and other measures to attain a zero-waste economy.

The research is focused on the context of India but it provides new details which can be helpful for other developing economies to relate. The research addresses the call for studies from public-sector and citizen’s perspectives to understand the acknowledgment of SWM systems and critical success factors using qualitative and exploratory method analysis.

The practical implications of the study include strict regulatory policies and guidelines for SWM acceptance, proper financial administration and benchmarking waste-recycling practices (prominent causal barriers). The practical implication of the results includes assistance in smart city projects in handling barriers proactively. The “Lack of Benchmarking processes” provides a critical application to standardized recycling practices in developing economies to improve the quality of the recyclable material/product. The comparative analysis also provides in-depth reflection toward the causal barriers from both the perspective which can help the government and stakeholders to work in a unified manner and establish an efficient waste management system. The results also conclude the need for targeted training programs and workshops for field implementation of innovative technologies to overcome the causal barrier. Moreover, policy-makers should focus to improve source segregation and recycling practices and ensure dedicated communication campaigns like Swachh Bharat Abhiyan to change the behavioral functioning of the community regarding waste. Lastly, developing economies struggle with the adequacy of resources to establish SWM systems, hence the authors conclude that proper financial planning is required at the ground level for smart city projects to overcome the spillover effects.

The social implications of the study include a reduction in pollution and efficient handling of waste resulting in a healthier and cleaner environment using IoT technology. Also, the results assist decision-makers in developing economies like India to establish smart city projects initiatives effectively to improve the quality of life. It proposes to establish standardized recycling processes for the better quality of recyclables and help in attaining a sustainable circular economy.

The research is novel as it provides comprehensive and comparative information regarding the barriers deferring SWM including the field barriers. To our consideration, the present study serves the first to address the comparative analysis of barriers in IoT-enabled waste systems and establish the relationship from both the perspective in middle-lower income economies. The study also suggests that the effect barriers can be overcome automatically by mitigating the causal barriers in the long run.

The main aim of this study is to understand the role of smart technologies and show the rankings of various smart technologies in collection and classification of electronic waste (e-waste).

This study presents a framework integrating the concepts of collection and classification mechanisms and smart technologies. The criteria set includes three main, which are economic, social and environmental criteria, including a total of 15 subcriteria. Smart technologies identified in this study were robotics, multiagent systems, autonomous tools, smart vehicles, data-driven technologies, Internet of things (IOT), cloud computing and big data analytics. The weights of all criteria were found using fuzzy analytic network process (ANP), and the scores of smart technologies which were useful for collection and classification of e-waste were calculated using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR).

The most important criterion was found as collection cost, followed by pollution prevention and control, storage/holding cost and greenhouse gas emissions in collection and classification of e-waste. Autonomous tools were found as the best smart technology for collection and classification of e-waste, followed by robotics and smart vehicles.

The originality of the study is to propose a framework, which integrates the collection and classification of e-waste and smart technologies.

Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.

The rapid technological growth, changes in consumer demands, products’ built-in obsolescence, presence of more non-repairable parts, shorter lifespan, etc., lead to the generation of e-waste at an unprecedented rate. Although a number of research proposals and business products to manage e-waste exist in the literature, they lack in many aspects such as incomplete coverage of product’s life cycle, access control, payment channels (in few cases), incentive mechanisms, scalability issues, and missing experimental validation. The purpose of this paper is to introduce a novel blockchain-based e-waste management system aiming to mitigate the above-mentioned downsides and limitations of the existing proposals.

This paper proposes a robust and reliable e-waste management system by leveraging the power of blockchain technology, which captures the complete life cycle of e-products commencing from their manufacturing as new products to their disposal as e-waste and their recycling back into raw materials.

While the use of blockchain technology increases accountability, transparency and trust in the system, the proposal overcomes various challenges and limitations of the existing systems by providing seamless interactions among various agencies.

This paper presents a prototype implementation of the system as a proof-of-concept using solidity on the Ethereum platform and this paper performs experimental evaluations to demonstrate its feasibility and effective performance in terms of execution gas cost and transaction throughput.

Currently, Mauritius is adopting landfilling as the main waste management method, which makes the waste sector the second biggest emitter of greenhouse gas (GHG) in the country. This presents a challenge for the island to attain its commitments to reduce its GHG emissions to 30% by 2030 to cater for SDG 13 (Climate Action). Moreover, issues like eyesores caused by littering and overflowing of bins and low recycling rates due to low levels of waste segregation are adding to the obstacles for Mauritius to attain other SDGs like SDG 11 (Make Cities & Human Settlements Inclusive, Safe, Resilient & Sustainable) and SDG 12 (Guarantee Sustainable Consumption & Production Patterns). Therefore, together with an optimisation of waste collection, transportation and sorting processes, it is important to establish a solid waste characterisation to determine more sustainable waste management options for Mauritius to divert waste from the landfill. However, traditional waste characterisation is time consuming and costly. Thus, this chapter consists of looking at the feasibility of adopting machine learning to forecast the solid waste characteristics and to improve the solid waste management processes as per the concept of smart waste management for the island of Mauritius in line with reducing the current challenges being faced to attain SDGs 11, 12 and 13.

The COVID-19 pandemic has affected around 216 countries and territories worldwide and more than 2000 cities in India, alone. The smart cities mission (SCM) in India started in 2015 and 100 smart cities were selected to be initiated with a total project cost of INR 2031.72 billion. Smart city strategies play an important role in implementing the measures adopted by the government such as the issuance of social distancing regulations and other COVID-19 mitigation strategies. However, there is no research reported on the role of smart cities strategies in managing the COVID-19 outbreak in developing countries.

This paper aims to address the research gap in smart cities, technology and healthcare management through a review of the literature and primary data collected using semi-structured interviews.

Each city is unique and has different challenges, the study revealed six key findings on how smart cities in India managed the COVID-19 outbreak. They used: Integrated Command and Control Centres, Artificial Intelligence and Innovative Application-based Solutions, Smart Waste Management Solutions, Smart Healthcare Management, Smart Data Management and Smart Surveillance.

This paper contributes to informing policymakers of key lessons learnt from the management of COVID-19 in developing countries like India from a smart cities’ perspective. This paper draws on the six Cs for the implications directed to leaders and decision-makers to rethink and act on COVID-19. The six Cs are: Crisis management leadership, Credible communication, Collaboration, Creative governance, Capturing knowledge and Capacity building.

As the world continues to urbanise, cities face increasing pressure to become more sustainable, efficient and livable. Sustainable smart cities are emerging as a promising solution to this challenge, leveraging technology and data to improve urban systems and services while reducing environmental impact. This chapter provides an overview of the concept of sustainable smart cities and its implications for urban development. It explores the key features of sustainable smart cities, including their focus on technology, data and citizen engagement and the challenges they are facing in terms of infrastructure, data management, social equity, environmental sustainability, governance and regulations. The chapter also highlights the implications of sustainable smart cities for urban planners, policymakers and other stakeholders, emphasising the need for collaborative approaches that engage citizens and stakeholders in the design and implementation of smart city initiatives.

The Internet of Things (IoT) is a cloud system that saves energy by being involved in the decision-making process of machines. By this means, machines create an environment of direct interaction without the need for explicit instructions. In this chapter, answers have been sought to the questions of what kind of research has been done on IoT-based technological devices, and how IoT-based technologies are effective in sustainable food production. The systematic literature review examined the scientific research on IoT and Food in the range of 2010–2022 in Scopus. The general framework of the research has been carried out in the context of 6Ws (who, when, where, what, why, and how), which is one of the systematic literature reviews. The results obtained have been analyzed and interpreted in the MAXQDA 2020 qualitative data analysis program. In the findings obtained, it has been determined that IoT and food have gained importance worldwide, especially in England, India, and China. Furthermore, it has been determined that most of the studies on IoT are based on case studies, and all the articles examined are collected in three main focus points. Subcodes have been created under the main codes ‘Food Supply Chain, Smart and Sustainable Agriculture ve Waste Management’, and problem points have been tried to be customized.

With the ever-growing population in the urban areas, the concept of smart cities started to be more present in the literature. Smart cities are seen as a solution that will respond to the needs of providing a sustainable place for living, and at the same time improving residents’ lives. To achieve this, various information and communication technologies (ICTs) are exploited, making the digitalization in the modern world of an immense importance. Advanced digital technologies enable the transformation of existing and the creation of new business models, the development of new products and services, increase the efficiency and competitiveness of the economy, and contribute to wider socio-economic development. Digitization of society and the economy through innovative and intensive use of ICTs has great potential for growth and is the basis for further development and competitiveness. This all generates an enormous amounts of data sets from which useful information are generated and used again the decision support systems. This chapter presents two examples from Slovenia where big data is used for improving residents’ lives, as part of the strategies for smart cities.