The future of waste management in smart and sustainable cities: A review and concept paper

Japanese public perceptions on smart bin potential to support PAYT systems

Smart bins can increase transparency and accuracy in monitoring waste characteristics such as weight, volume, and disposal times. This information can aid in enforcing waste reduction policies, including the pay-as-you-throw (PAYT) system. However, the public's response to this technology remains uncertain. Despite Japan's reputation for high waste separation compliance and collection rates, it has one of the world's highest per capita rates of plastic and packaging waste generation. This study surveyed 1000 Japanese individuals regarding their perception of smart bin features and their potential to encourage waste reductions. Multiple correspondence analysis (MCA) was used to explore the relationships between respondents' social attributes and their responses. The findings indicate a slightly higher responses from younger respondents (above 85 % of those age 10-29 compared to around 75 % of those aged 60 and older) who were in favour of smart bin technology functions such as unscheduled waste pick up and automatized waste separation. On the other hand, there was a strong unwillingness (0.57 count ratio) to reduce plastic waste even if a smart bin assisted PAYT is introduced from those who did not engage in waste separation and cleaning in the first place. Finally, an open-ended question about strategies to reduce plastic waste resulted in a large portion of mindset change ideas (24.8 % of the female respondents) and technology innovations proposals (24 % of male respondents). Although development of a smart-bin prototype is taking place, behavioral change strategies to foster a willingness to reduce waste must take place along with technological interventions.

How does the digital economy affect the provincial "zero-waste city" construction? Evidence from China

The digital economy is playing a crucial effect in the field of environmental governance. Digital and intelligent management is an essential means to fully realize the "zero-waste city" construction. The present paper investigates the impact of digital economy on China's provincial "zero-waste city" construction. The results indicate that digital economy can contribute to "zero-waste city" construction. The digital economy has a positive nonlinear effect on the construction of "zero-waste city," but the marginal effect is diminishing. The digital economy can facilitate "zero-waste city" construction by improving industrial structure upgrading and green technology innovation. Heterogeneity analysis reveals that digital economy contributes to the construction of "zero-waste city" in the eastern and western regions and high-level environmental regulation regions, while this impact is insignificant in the central region and low-level environmental regulation regions. The digital economy exerts the most significant positive influence on waste resource recycling followed by waste final disposal and then waste reduction at the source. These findings underscore the effect of digital economy in fostering "zero-waste city" construction and promoting sustainable waste management. The present study provides new ideas for the "zero-waste city" construction in emerging developing countries such as China.

Exploring the transformative power of AI in art through a circular economy lens. A systematic literature review

Today, technology and sustainability are two strategic axes for the development of any industry. Art is no exception and embodies both principles. Artificial intelligence (AI) is driving the art world forwards with its applications and algorithms. Additionally, the circular economy (CE) is concerned with resources and the environment in this context. The objective of the present work is to provide an overview of the current state of research on the application of AI in the art world and an analysis of how CE principles are being incorporated, considering the interactions between AI and the CE. To this end, a systematic review of the literature is carried out in which 60 articles related to the subject are selected, analysed, and classified, highlighting the lines of research addressed. The assessment of the current state of research on the subject concludes with the four main axes of classification of works. The first line is related to AI generative content in art, addressing issues of content creation, image and painting, video, and theatre. The second line is related to AI applications for art industry production, considering the sustainability of the supply chain. The third line focuses on how the CE is being applied to art, while the fourth line focuses on other relevant aspects analysed, such as training and design. The topic is still incipient, mandating further research to study the full potential of AI and the CE in the world of art.

Smart waste management 4.0: The transition from a systematic review to an integrated framework

Smart Waste Management (SWM) discusses the waste management process for different types of waste while introducing an intelligent approach to controlling the amount of waste. This paper introduces SWM4.0, which applies Industry4.0 (I4.0) technologies in various related events. First, the paper presents a systematic literature review on the role of I4.0 technologies in SWM activities regarding waste types, waste management processes, and 5R strategies. Then, existing solutions supporting SWM4.0 are extracted to develop a framework for exploring the use of I4.0 technologies. This framework includes sharing the four main pillars that contribute to the success of SWM4.0, namely smart people, smart cities, smart enterprises, and smart factories. Furthermore, this review suggests the possibility of unifying and extending existing solutions and identifying the necessary links and interfaces for researchers. For managerial implications, the framework identifies future strategies to fulfill specific SWM tasks and to foster new technological solutions for future research.

Assessment of inorganic solid waste management techniques using full consistency and extended MABAC method

Population and industrial growth have spiked product consumption, which in turn have caused an abrupt rise in municipal solid waste (MSW) production. Due to the lack of resources allocated to waste management, municipal inorganic solid waste (ISW) has increased exponentially, posing a significant strain on the environment and health. To mitigate these issues, sustainable waste management strategies need to be implemented to reduce environmental impacts and improve waste collection and disposal efficiency. The objective of our work was to analyse and identify the most effective techniques for disposing of ISW in India by employing multi-criteria decision-making (MCDM). This technique entails selecting the most suitable alternative based on a variety of competing and interactive criteria. A fusion decision model named the FULL COnsistency Method (FUCOM) and Multi-Attributive Border Approximation area Comparison (MABAC) based on the interval-valued q-rung orthopair fuzzy (IV q-ROF) was developed. Finally, a comparative analysis was performed to demonstrate the system's robustness.

Smart technological options in collection and transportation of municipal solid waste in urban areas: A mini review

The rapid increase in quantities and the mismanagement of municipal solid waste (MSW) in developing countries are increasing the environmental impacts such as air, water and soil contamination. The present scenario of MSW management deals with numerous issues such as lack of technological resources, strategical management, social awareness, public participation, etc. Globally, numerous efforts in the form of new policies, schemes and regulatory acts have been made to develop a systematic collection and transportation (C&T) method using advanced, integrated technologies. However, very few studies have addressed this issue for low- and middle-income countries due to the lack of availability of reliable resources and data sets. This paper addresses the present challenges in C&T methods and highlights the application of information communication technology in monitoring, capturing, data management, planning, live tracking and communication. This systematic mini-review is based on the availability of technical resources, consumer acceptance and cost-effectiveness of different technologies in managing the processes. The study revealed that the C&T methods in most developed countries are designed based on their geographical stretch, climatic factors, waste characteristics and compatible technology, resulting in sustainable MSW management. However, developing countries have followed the same monotonous approach in managing their MSW, which fails in C&T process. The case study provides a valuable resource for researchers and policymakers to frame a better C&T process based on the recent technological interventions, infrastructure development, and social and economic status.

An innovative medical waste management system in a smart city using XAI and vehicle routing optimization

Background

The management of medical waste is a complex task that necessitates effective strategies to mitigate health risks, comply with regulations, and minimize environmental impact. In this study, a novel approach based on collaboration and technological advancements is proposed.

Methods

By utilizing colored bags with identification tags, smart containers with sensors, object recognition sensors, air and soil control sensors, vehicles with Global Positioning System (GPS) and temperature humidity sensors, and outsourced waste treatment, the system optimizes waste sorting, storage, and treatment operations. Additionally, the incorporation of explainable artificial intelligence (XAI) technology, leveraging scikit-learn, xgboost, catboost, lightgbm, and skorch, provides real-time insights and data analytics, facilitating informed decision-making and process optimization.

Results

The integration of these cutting-edge technologies forms the foundation of an efficient and intelligent medical waste management system. Furthermore, the article highlights the use of genetic algorithms (GA) to solve vehicle routing models, optimizing waste collection routes and minimizing transportation time to treatment centers.

Conclusions

Overall, the combination of advanced technologies, optimization algorithms, and XAI contributes to improved waste management practices, ultimately benefiting both public health and the environment.

Experimental investigation and multi-performance optimization of the leachate recirculation based sustainable landfills using Taguchi approach and an integrated MCDM method

Landfill leachates contain harmful substances viz. chemicals, heavy metals, and pathogens, that pose a threat to human health and the environment. Unattended leachate can also cause ground water contamination, soil pollution and air pollution. This study focuses on management of leachate, by recirculating the rich, nutrient-filled fluid back into the landfills, turning it to a bioreactor, thereby maximising the performance parameters of landfills favourable for electricity production by the waste to energy plants. This study demonstrates a sustainable alternative method for utilising the fluid, rather than treating it using an extremely expensive treatment process. Further, it also experimentally investigates the effect of varying levels of five input parameters of the landfill including waste particle size, waste addition, inorganic content in waste, leachate recirculation rate, and landfill age, each at five levels, on the multiple performance of the landfill using Taguchi's L25 standard orthogonal array. Experimental results are analysed using an integrated MCDM approach i.e. MEREC-PIV method and statistical techniques such as analysis of mean (ANOM) and analysis of variance (ANOVA). The results indicate that the optimal setting of the input parameters is waste particle size at 9 ppm, waste addition at 80 Ktoe, inorganic content in waste at 2%, leachate recirculation rate at 250 l/day and landfill age at 3 years. Further, inorganic content waste is found to be the most significant parameter for the multiple performance of the landfill. This study presents a novel approach to produce input parameters for power plants which may enhance their profitability and sustainability.

Identifying the influencing factors and constructing incentive pattern of residents' waste classification behavior using PCA-logistic regression

With the acceleration of urbanization, domestic waste has become one of the most inevitable factors threatening the environment and human health. Waste classification is of great significance and value for improving urban environmental quality and promoting human well-being. Based on the theory of planned behavior, we added external and socio-economic factors to systematically examine how they affect residents' waste classification behavior (WCB). We collected 661 valid data through a questionnaire survey conducted in Jinan, a pilot city for waste classification in China. Key driving factors were identified by combining binary logistic regression and the principal component analysis. The results showed that the elderly, women, and people with higher education are more likely to participate in waste classification. Attitude, collaborative governance, and institutional pressure positively affect WCB, while subjective norm and infrastructure have a negative effect. Knowledge mastery and degree of publicity are positively and significantly related to WCB, but other perceived behavioral control sub-variables negatively affect WCB. Based on the results and status of waste classification in Jinan, we propose the multi-agent linkage governance pattern from various dimensions to explore a powerful guiding incentive that can enhance WCB and provide a reference for waste management policymakers.

Smart technologies for collection and classification of electronic waste

Purpose

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).

Design/methodology/approach

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).

Findings

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.

Originality/value

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

Modelling of the Process of Extrusion of Dry Ice through a Single-Hole Die Using the Smoothed Particle Hydrodynamics (SPH) Method

This article presents the outcome of research on modelling the process of the extrusion of crystalline dry ice. The purpose of this process is to densify the material and obtain pellets of several millimeters in diameter. This reduces the sublimation rate in ambient conditions of the material whose temperature in a solid state is 195 K. A lower sublimation rate means a reduction of the loss of product in its final applications, which include refrigeration and reduction of atmospheric emissions of gaseous CO₂. A ram-type extruder was considered in this analysis, in which dry ice was extruded through a single-hole die of varying geometry. The article presents the results of numerical analyses of the extrusion process, using a simulation method based on the Smoothed Particle Hydrodynamics (SPH) approach. The results from simulations were verified by the experimental data in terms of the maximum force required to complete the process, in order to assess the applicability of the proposed method in further research on dry ice compression.

Socioeconomic and resource efficiency impacts of digital public services

This paper measures the socioeconomic and resource-efficient influences of digital transformation in the public sector in the European region. To capture the socioeconomic impacts of digital public services, we employ a socioeconomic score index calculated as the unweighted average of the re-scaled scores for changes in employment, exports, and turnover from eco-industries. Regarding resource-efficient impacts, we employ the resource efficiency score index measured as the unweighted average of the re-scaled scores for material, energy productivity, and the intensity of greenhouse gas (GHG) emissions. Measures such as user-centricity, business mobility, and key enablers are used to demonstrate the level of digitalization in the public sector. According to our estimations based on various econometric techniques, digital public services have a favorable effect on the economy and society through a positive impact on employment, exports, and turnover of eco-industries. The effects of digitalization on resource productivity follow a nonlinear U-shaped curve, suggesting that the improvement of resource efficiency is only present when the digital transformation process reaches a certain level.

Analyzing failures in adoption of smart technologies for medical waste management systems: a type-2 neutrosophic-based approach

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.

Ecosystem service deficits of European cities

Climate change and biodiversity loss are two pressing global environmental challenges that are tightly coupled to urban processes. Cities emit greenhouse gases through the consumption of materials and energy. Urban expansion encroaches on local habitats, while urban land teleconnections simultaneously degrade distant ecosystems. These processes decrease the supply of and increase the demand for ecosystem services inside and outside urban areas. Most cities are in a state of ecosystem services deficit, whereby demand exceeds local supply of ecosystem services. Methods to quantify this deficit by capturing multi-scale and multi-level ecological exchanges are incipient, leaving scholars with a partial understanding of the environmental impacts of cities. This paper deploys a novel method to simulate future urban supplies and demands of two key ecosystem services needed to combat climate change and biodiversity loss - global climate regulation and global habitat maintenance. Applying our model to eight representative European cities, we project growing ecosystems deficits (demand exceeds supply) between 8% and 214% in global climate regulation and 11% and 431% in global habitat maintenance between 2020 and 2050. Variation between cities stems from differing dietary patterns and electricity mixes, which have large implications for ecosystems outside the city. To combat these losses, urban sustainability strategies should complement local restoration with changes to local consumption alongside promoting remote ecological restoration to tackle the multi-level environmental impacts of cities.

Techno-economic and environmental assessments for sustainable bio-methanol production as landfill gas valorization

With the regular increase in global solid waste, landfilling is intensively used for waste disposal. However, landfill gas (LFG) produced as a byproduct during waste decomposition in the landfills is a serious problem since it leads to damage to the eco-systems. Accordingly, it has been highlighted to convert LFG into other value-added chemicals. In this study, LFG utilization was studied in terms of conversion into methanol (MeOH) by considering different scenarios of LFG utilization. Techno-economic analysis and environmental assessment were performed to identify the economic feasibility and environmental impact of each case. From the economic analysis, bio-MeOH production costs of 879.16, 724.52, and 1,130.74 $ ton^-1 for case 1, 2, and 3 was estimated with the economic infeasibility, while substantial cost reduction through projected cost analysis can lead to economic competitiveness (449.52 $ ton^-1 for case 2 and 595.76 $ ton^-1 for case 3). In sequence, the quantitative environmental impacts in terms of climate change impact were 2.360, 0.835, and 0.605 kg CO₂-eq kg MeOH^-1 for cases 1, 2, and 3, respectively. Based on the results of two analyses, a multi-criteria decision analysis was conducted to investigate the acceptable case of bio-MeOH production in the economic and environmental aspects. It can be concluded that the most feasible case depends on decision-makers if only economic and environmental criteria were considered. Therefore, dry reforming and membrane separation of LFG have considerable potential for bio-MeOH production in terms of LFG utilization for high weighting of economic and environmental aspects, respectively.

Digitalization of waste management: Insights from German private and public waste management firms

Policymakers, practitioners, and scholars have long-lauded digital technologies, such as smart waste containers or artificial intelligence for material recognition and robotic automation, as key enablers to more effective and efficient waste management. While these advances promise an increasingly digitalized future for collecting, sorting, and recycling waste material, little is known about the current extent of digitalization by waste management firms. Available studies focus on firms' digitalization intentions, largely neglecting the level of actual adoption of digital technologies, and do not differentiate the level of digitalization alongside different steps of the waste management value chain. Our study reports on a cross-sectional descriptive survey that captures current digitalization efforts and strategies of 130 public and private waste management firms in Germany. We analyze their levels of digitalization along with different steps of the waste management value chain, explore their different objectives, approaches, and transformational measures with regard to digitalization. Our findings reveal that while the perceived importance of digitalization in the waste management sector continues to grow, the actual adoption of advanced digital technologies falls notably behind intentions reported in 2016 and 2017. We explore the reasons for this gap, point out so far largely ignored research opportunities, and derive recommendations for waste management firms and associations.

A Review of Future Household Waste Management for Sustainable Environment in Malaysian Cities

In recent years, Malaysia has faced environmental challenges caused by municipal solid waste, especially household waste, during the COVID-19 pandemic. Among all the household waste, plastic and paper are the most unmanaged waste that cause environmental issues. Several recycling associations in Malaysia have carried out their practices for better waste sustainability and management to curb the increasing amount of household waste. However, the effectiveness is still vague in achieving smart and effective household waste management. Therefore, this paper aims to investigate Malaysia’s household waste management, mainly in three significant municipalities in Malaysia, namely Kuala Lumpur, Penang, and Melaka, in becoming a resilient and sustainable city by addressing two main research questions: (1) What are the key factors for ensuring the more successful moves for future household waste management in cities? and (2) How do each of the three municipalities of Malaysia cities address their waste issues based on the key factors from RQ1? This paper reviewed 13 waste management articles and explores the potential of the four factors of waste management from the perspective of technology and data, economy, social, and governance. The discussed factors and models contributed to an integrated future-proofing framework that focuses on smart waste tracking, a gamified awareness education, and strict policies to control waste management are the way forward for the future of smart cities household waste management.

A facilitating framework for a developing country to adopt smart waste management in the context of circular economy

To achieve higher standards of sustainability, the waste management sector now requires the incorporation of circular economy (CE) principles. However, an easy transition toward the particular goal would require the use of smart waste technologies. To achieve the aforementioned goal, this study aims to provide a facilitating framework for the adoption of smart waste management in the context of CE for Pakistan. To help Pakistan transition toward the new paradigm, a total of 16 critical facilitators are evaluated based on five distinctive criteria using a novel fuzzy hybrid multi-criteria decision-making (MCDM) approach. The hybrid MCDM approach includes fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) for allocating weights to the determined criteria; whereas, the fuzzy VIšekriterijumsko kompromisno rangiranje (VIKOR) approach is used to rank the critical facilitators adopted from the secondary literature. The fuzzy approach in both cases is to deal with any kind of uncertainty during the data collection process. Based on the achieved results, the study suggests that before the application of smart waste technologies in the country, Pakistan should first focus on devising regulations that effectively address the mismanagement of waste produced in the country. Also, the industries in the country need to become more responsible and should adopt environmental management systems that foster waste minimization. Lastly, the country in the third phase should focus on the wide application of digitalization both in the streams of ICT and IoT, for collecting, sharing, and receiving waste data. The study further provides policy recommendations to the respective stakeholders that will help the country achieve zero-waste CE.

People-Centred Development of a Smart Waste Bin

The study presented in this article focuses on the role of a smart waste bin (waste container) designed for waste management and explores what types of interventions people consider more appropriate in promoting environmentally responsible behaviour—based on norms or on an individual’s emotions. The smart waste bin development process was people-centred and paid particular attention to human experiences, allowing for various interaction modalities. By incorporating various sensors for waste volume and weight measurement in conjunction with presence and user identification capabilities, the experience was personalised. User feedback was collected by an extensive survey, consisting of four systematic sections, where values, attitudes, norms, perceived behavioural control, behavioural intention and actual behaviour were examined. The survey was completed by 194 respondents. The results showed that participants at the declarative level show a high level of environmental awareness and are very much willing to handle waste appropriately. Additionally, the results of the R&D process indicated that relatively cheap and efficient technological solutions can be developed to support waste management and sustainable lifestyles if the human-centred approach is taken into account.

Recycling behaviour: Mapping knowledge domain through bibliometrics and text mining

In recent years, the research on human behaviour in relation to waste management has increased at an exponential rate. At the same time, the expanding academic literature on this topic makes it more difficult to understand the main areas of interest, the leading institutions and authors, the possible interconnections among different disciplines, and the gaps. This paper maps knowledge domain on recycling behaviour through bibliometric analysis and text mining in order to identify current trends, research networks and hot topics. 2061 articles between 1975 and 2020 from three different databases are examined with an interdisciplinary approach. The findings reveal that 60% of papers have been published between 2015 and 2020, and this topic is of global interest. Leading countries are mainly located in Europe, North America and Commonwealth; however, China and Malaysia are also assuming a driving role. Bibliometrics and text mining provide the intellectual configuration of the knowledge on recycling behaviour; co-word analysis individuates conceptual sub-domains in food waste, determinants of recycling behaviour, waste management system, waste electrical and electronic equipment (WEEE), higher-level education, plastic bags, and local government. Overall, waste management and related human behaviour represent a universal challenge requiring a structured and interdisciplinary approach at all levels (individual, institutions, industry, academia). Lastly, this paper offers some suggestions for future research such as smart city design, sensor network system, consumer responsibilisation, the adoption of a more comprehensive view of the areas of investigation through the holistic analysis of all stakeholders.

Emerging Technologies for Smart Cities’ Transportation: Geo-Information, Data Analytics and Machine Learning Approaches

With the recent increase in urban drift, which has led to an unprecedented surge in urban population, the smart city (SC) transportation industry faces a myriad of challenges, including the development of efficient strategies to utilize available infrastructures and minimize traffic. There is, therefore, the need to devise efficient transportation strategies to tackle the issues affecting the SC transportation industry. This paper reviews the state-of-the-art for SC transportation techniques and approaches. The paper gives a comprehensive review and discussion with a focus on emerging technologies from several information and data-driven perspectives including (1) geoinformation approaches; (2) data analytics approaches; (3) machine learning approaches; (4) integrated deep learning approaches; (5) artificial intelligence (AI) approaches. The paper contains core discussions on the impacts of geo-information on SC transportation, data-driven transportation and big data technology, machine learning approaches for SC transportation, innovative artificial intelligence (AI) approaches for SC transportation, and recent trends revealed by using integrated deep learning towards SC transportation. This survey paper aimed to give useful insights to researchers regarding the roles that data-driven approaches can be utilized for in smart cities (SCs) and transportation. An objective of this paper was to acquaint researchers with the recent trends and emerging technologies for SC transportation applications, and to give useful insights to researchers on how these technologies can be exploited for SC transportation strategies. To the best of our knowledge, this is the first comprehensive review that examines the impacts of the various five driving technological forces—geoinformation, data-driven and big data technology, machine learning, integrated deep learning, and AI—in the context of SC transportation applications.

Smart Sustainable City Roadmap as a Tool for Addressing Sustainability Challenges and Building Governance Capacity

Building smart sustainable cities initiatives requires governance capacity, which is constantly challenged by a diversity of actors and the transformation towards a digital society; however, the process of identifying the conditions for building a smart sustainable city (SSC) is not straightforward. As an attempt to map the key governance conditions, the goal of this study is to suggest guidelines for the development of SSC initiatives in the format of a generic roadmap. This research applies design science research methodology and builds the roadmap based on identified antecedents that may hinder or facilitate the development of SSC initiatives from a systematic literature review and the analysis of key governance aspects from 12 smart city initiatives in Europe and Latin America. This paper builds its results through a four-step approach including: (1) defining the main concepts and dimensions within the smart sustainable city context; (2) identifying sustainability challenges for the development of smart sustainable city initiatives; (3) analysing key governance aspects from smart sustainable city initiatives; and (4) designing an actionable research-based roadmap and practical recommendations. The resulting roadmap contains 11 key governance conditions for developing strategies for smart sustainable city initiatives that were classified into three main phases: (1) planning; (2) implementing; and (3) adopting, monitoring, and evaluating. In terms of contribution, this research provides a tool to support the development of initiatives, addressing sustainability challenges and strengthening governance capacity to ensure the long-term impacts of smart sustainable cities.

The Key Organizational Factors in Healthcare Waste Management Practices of Libyan Public Hospitals

This study aims to investigate factors contributing to healthcare waste management practices among Libyan public hospitals. The organizational culture and structure are proposed to have their effect upon hospital organizational units in charge of healthcare waste production by a theoretical review to develop two main hypotheses. Hence, this study used the stratified random sampling technique to select respondents such as top management officials, heads of departments, and administrators who work in all the hospitals located in the south of Libya, from whom data was collected. The data for the study was gathered via a survey questionnaire from Libyan public hospitals in the country’s southern region. A total of 210 questionnaires were distributed and 171 usable responses were received, yielding a 70% response rate. Though the findings of the study show some inconsistency, the two dimensions of the culture examined in this study are found to have a positive relationship and significant influence on the management practices of health waste. Besides, it shows the positive relationship between organizational structure and healthcare waste management practices (HWMP). However, the findings of this study suggested that nurses and cleaners’ practices should critically consider structure dimensions such as formalization as well as moderating variables such as hospital location and type of services supplied on the interactions to improve the management of healthcare waste in Libya’s public hospitals.

Innovation Trajectories for a Society 5.0

Big Data, the Internet of Things, and robotic and augmented realities are just some of the technologies that belong to Industry 4.0. These technologies improve working conditions and increase productivity and the quality of industry production. However, they can also improve life and society as a whole. A new perspective is oriented towards social well-being and it is called Society 5.0. Industry 4.0 supports the transition to the new society, but other drivers are also needed. To guide the transition, it is necessary to identify the enabling factors that integrate Industry 4.0. A conceptual framework was developed in which these factors were identified through a literature review and the analytical hierarchy process (AHP) methodology. Furthermore, the way in which they relate was evaluated with the help of the interpretive structural modeling (ISM) methodology. The proposed framework fills a research gap, which has not yet consolidated a strategy that includes all aspects of Society 5.0. As a result, the main driver, in addition to technology, is international politics.

Assessment of urban solid waste management systems for Industry 4.0 technology interventions and the circular economy

The ongoing fourth industrial revolution, Industry 4.0 (I4.0), is transforming various industries across the globe. At the same time, resource scarcity with high consumption rates has led to the development of the circular economy. Both concepts advocate for sustainable growth and waste minimization. In developing countries, the integrated solid waste management framework is undergoing modification under I4.0 and the circular economy. Urban local bodies are often unable to measure the readiness of their waste management systems to transform under I4.0 and the circular economy. Here the novel concept of Waste 4.0 is developed. 'Waste 4.0' is a readiness assessment tool to promote the comprehensive transformation of municipal solid waste management under I4.0 and circular economy. This tool has eight determinants for assessing the municipal solid waste management of urban local bodies. To validate Waste 4.0 the urban local bodies of Indore and Sagar, India were used as case studies. The readiness index for I4.0 in the municipal solid waste management system in Indore and Sagar was 0.72 and 0.14, respectively. The readiness index for circular economy focus in Indore and Sagar was 0.65 and 0.13, respectively. The Indore urban local body was classified as an 'Experienced' player for I4.0 Intervention and a 'circular economy fast adopter' for circular economy focus under I4.0 readiness. The Sagar urban local body was classified as a 'Hesitator' player for I4.0 Intervention and achieved the 'Business as usual' tag for circular economy focus under I4.0 readiness. With the Waste 4.0 assessment results urban local bodies can better plan and thus transform their municipal solid waste management systems under I4.0 and the circular economy.

Behavioral change in waste separation at source in an international community: An application of the theory of planned behavior

Analysing and understanding the factors that influence the behavior of waste separation is critical to improved waste management. This study identified the factors behind behavioral change in waste separation at source in an international community. The theory of planned Behavior (TPB) was adopted to conduct a self-report questionnaire survey twice, in which 354 residents participated at Time1 and 331 at Time 2, with a retention rate of 93.5%. The questionnaires were designed based on TPB with additional questions regarding waste separation rules in the community, experience of waste separation, and environmental knowledge. With the questionnaire data and follow-up qualitative interviews, factors related to waste separation through factor analysis and structural equation modelling and text mining were specified. The panel data collected over three months demonstrated the changes in attitudes, subjective norms, and perceived behavioral control that affect behavioral intention in the process of behavior adaption. Combined with interview data, the reasons for these changes can be further attributed to individuals' environmental knowledge and community guidelines. The findings imply that policies targeting environmental education and rulemaking are effective to help residents form more positive intentions towards waste separation.

Designing of reverse vending machine to improve its sorting efficiency for recyclable materials for its application in convenience stores

Plastics have multiple applications in disposable products, high-end technology parts, etc., owing to their functionality and manufacturing flexibility. However, their increased use has increased the global proportion of plastic wastes, which creates a serious environmental issue, thereby, creating a demand for plastic waste management techniques. Improving the efficiency of resource recovery by appropriate sorting and collection systems is necessary for successful plastic recycling. Therefore, this study proposed a three-step optimization process of a reverse vending machine (RVM), a small automatic recyclable waste sorter/collector system, for acquiring an optimal design and enhanced efficiency. The RVM system categorized recyclable wastes as plastics, glass, and cans using barcode, vision, and near infrared sensors. The average sorting efficiency of the designed RVM system was 94%, 95% for polyethylene terephthalate, and 98% for glass bottles. Therefore, the RVM system, with the average sorting efficiency of 95%, is suitable for application in on-site sorting in small-sized areas, such as convenience stores, which generate wastes on a small scale.Implications: This study proposed a three-step optimization process of a reverse vending machine (RVM), a small automatic recyclable waste sorter/collector system, for acquiring an optimal design and enhanced efficiency. The RVM system is suitable for application in on-site sorting in small-sized areas, such as convenience stores, which generate wastes on a small scale.

Sensors for Sustainable Smart Cities: A Review

Experts confirm that 85% of the world’s population is expected to live in cities by 2050. Therefore, cities should be prepared to satisfy the needs of their citizens and provide the best services. The idea of a city of the future is commonly represented by the smart city, which is a more efficient system that optimizes its resources and services, through the use of monitoring and communication technology. Thus, one of the steps towards sustainability for cities around the world is to make a transition into smart cities. Here, sensors play an important role in the system, as they gather relevant information from the city, citizens, and the corresponding communication networks that transfer the information in real-time. Although the use of these sensors is diverse, their application can be categorized in six different groups: energy, health, mobility, security, water, and waste management. Based on these groups, this review presents an analysis of different sensors that are typically used in efforts toward creating smart cities. Insights about different applications and communication systems are provided, as well as the main opportunities and challenges faced when making a transition to a smart city. Ultimately, this process is not only about smart urban infrastructure, but more importantly about how these new sensing capabilities and digitization developments improve quality of life. Smarter communities are those that socialize, adapt, and invest through transparent and inclusive community engagement in these technologies based on local and regional societal needs and values. Cyber security disruptions and privacy remain chief vulnerabilities.

Potential Applications of 5G Network Technology for Climate Change Control: A Scoping Review of Singapore

Climate change is one of the most challenging problems that humanity has ever faced. With the rapid development in technology, a key feature of 5G networks is the increased level of connectivity between everyday objects, facilitated by faster internet speeds with smart facilities indicative of the forthcoming 5G-driven revolution in Internet of Things (IoT). This study revisited the benefits of 5G network technologies to enhance the efficiency of the smart city and minimize climate change impacts in Singapore, thus creating a clean environment for healthy living. Results revealed that the smart management of energy, wastes, water resources, agricultures, risk factors, and the economy adopted in Singapore can remarkably contribute to reducing climate change, thus attaining the sustainability goals. Hence, future studies on cost-effective design and implementation are essential to increase the focus on the smart city concept globally.

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.

Conceptualizing Core Aspects on Circular Economy in Cities

Currently, there are many different interpretations in the literature of what a circular economy is and how it functions. As cities are still facing challenges to become fully sustainable, the need for a comprehensive analysis of how the circular economy can be implemented in urban areas is increasing. This article aims at outlining circular cities by their key characteristics and to further explore and provide a framework for fostering circularity at the city level. In order to achieve this goal, we performed a systematic review and analyzed key papers published in the field of circular economy to determine how circular economy practices form circular cities. We discovered that cities play a focal role in facilitating the transition towards circularity through the closing of the loops, recirculation, technical innovation, policy elaboration and citizens’ support. However, city policymakers are still uncertain about how a circular city looks like and what its purpose is, as views are ranging from a strategic ambition to a niche concept of a smart city. Such uncertainty brings challenges, especially in the transition phase that many cities are in at the moment. This further implies that circular economy applied at the urban level still needs effort and innovation to successfully pass the transition phase from the linear economy. Therefore, lastly, we developed a framework model that can be adapted in other cities to facilitate their transition to circular cities.

The Impacts of the Fourth Industrial Revolution on Smart and Sustainable Cities

This article aims to analyze the impacts of the Fourth Industrial Revolution on the implementation of smart sustainable cities. For this purpose, a data mining process was conducted to analyze the terms that had a higher incidence in the literature in order to classify them by relevance and identify their interdependencies in the concepts of sustainable cities and smart cities. As a result, we highlight that the Fourth Industrial Revolution will have implications on several factors that are deeply connected to the success of cities in becoming sustainable: job creation, industries, innovation, environmental preservation, community involvement, and accessibility. In this context, policymakers will have opportunities and challenges that must be faced. Big data, the IoT, augmented reality, and simulations can have positive and negative externalities. Positive externalities include new information that could be mined, analyzed, and used for identifying previously unseen problems, the provision of new industrial innovations that can make economies thrive, helping promote inclusion for disabled people, as well as helping society to foresee problems and hence adapt to them in a timely manner.

Sustainable collection center location selection in emerging economy for electronic waste with fuzzy Best-Worst and fuzzy TOPSIS

In emerging economies, electronic waste is an important problem, because it negatively affects the health of staff and people, and causes pollution. Moreover, the location of the collection center has a crucial role in sustainable supply chains. Therefore, in this study, a framework was proposed to identify the location of sustainable collection centers for e-waste. The criteria set includes 3 main criteria, and 23 sub-criteria, and 7 different location options. The main criteria cover economic, social, and environmental criteria, which are organized as the Triple-Bottom-Line dimensions. Alternatives are Manisa, Menemen, Gaziemir, Kemalpaşa, Torbalı, Çiğli, and Akhisar. Fuzzy Best-Worst Method (BWM) and Fuzzy TOPSIS methods are used to calculate the weights of criteria and rankings of the alternatives, respectively. Transportation cost was found as the most important criterion for sustainable collection center selection, followed by collection cost, storage/holding cost, land cost, greenhouse gas emissions, energy cost, tax, and investment cost, respectively. Among other alternatives, Çiğli was found as the best alternative for sustainable collection center, followed by Gaziemir, and Manisa. Managerial implications were presented based on the findings.

Public health in times of crisis: An overlooked variable in city management theories?

The volume of research that associates the theme of city management with crises resulting from emerging infectious disease is modest, even after the occurrences of Ebola and Severe Acute Respiratory Syndrome. Similarly, the Coronavirus disease (COVID-19) pandemic has thus far contributed only modestly to the expansion of attention to people's health, through city management, in times of crisis. This study, by means of a systematic literature review, analyzes the gap in research on urban theory on how epidemics are confronted. The term "cities" had 2,440,607 articles published and were identified 665 that presents the combination of the term "pandemic". After the development of content analysis were identified 11 articles prior to 2019 and 10 articles published between January and June 2020, adhering to the objective of this investigation. Prior to 2019 studies addressed topics related to the construction of an urban structure aimed at reducing people's vulnerability to infectious diseases, starting in 2020, the focus of researchers' attention is on the use of information and communication technologies used as tools for prevention and control. Theories of the management of cities indicate the need to extrapolate the urban perimeter, incorporating the relations of dependence in cities with the other actors within the surroundings, especially in times of crisis. Studies have emphasized that cities are not isolated islands; rather, they are parts of a complex system with multiple exchanges. This thematic field of study enhances research that presents urban planning solutions by using data-driven management to consider conduct, parameters, and protocols relating to public health in moments of crisis.

Sustainable Waste Management for a City Multifloor Manufacturing Cluster: A Framework for Designing a Smart Supply Chain

This study focuses on integrated sustainable waste management (ISWM) within a city multifloor manufacturing (MFM) cluster. Manufacturing activities in residential areas of the urban environment and the associated generation of municipal production waste (MPW) are serious problems. The primary goal of this study is to design smart supply chain (SSC) scenarios for the shipment of MPW from a city MFM cluster under uncertainty. This paper presents a new model of the finite MPW generation capacity for a city MFM cluster on the basis of an analysis of its finite production capacity using the material flow analysis (MFA) methodology. The proposed model allows us to determine the number of transport fleet units needed for the implementation of various supply chain (SC) scenarios of MPW. To select the best scenario for MPW shipment in real time, the application of SSC and SSC management (SSCM) technologies is proposed. SSCM performance indicators are proposed which allow us to evaluate the efficiency of using vehicles for cluster MPW transportation. The numerical values of the SSCM performance indicators for various options regarding the handling of city MFM buildings using trucks are obtained. These evaluations form the basis for the decision-making and planning associated with the SSCs of MPW.

Towards a Smart E-Waste System Utilizing Supply Chain Participants and Interactive Online Maps

Efficient electronic waste (e-waste) management is one of the vital strategies to save materials, including critical minerals and precious metals with limited global reserves. The e-waste collection issue has gained increasing attention in recent years, especially in developing countries, due to low collection rates. This study aims to search for progressive solutions in the e-waste collection sphere with close-to-zero transport and infrastructure costs and the minimization of consumers’ efforts towards an enhanced e-waste management efficiency and collection rate. Along these lines, the present paper develops a smart reverse system of e-waste from end-of-life electronics holders to local recycling infrastructures based on intelligent information technology (IT) tools involving local delivery services to collect e-waste and connecting with interactive online maps of users’ requests. This system considers the vehicles of local delivery services as potential mobile collection points that collect and deliver e-waste to a local recycling enterprise with a minimum deviation from the planned routes. Besides e-waste transport and infrastructure costs minimization, the proposed smart e-waste reverse system supports the reduction of CO2 through the optimal deployment of e-waste collection vehicles. The present study also advances a solid rationale for involving local e-waste operators as key stakeholders of the smart e-waste reverse system. Deploying the business model canvas (BMC) toolkit, a business model of the developed system has been built for the case of Sumy city, Ukraine, and discussed in light of recent studies.

Cost analysis and optimization of Blockchain-based solid waste management traceability system

As global concerns over End-of-Life (EoL) wastes released to the environment is rising, the need for enhancing the transparency of recycling systems is growing. To address the waste traceability issue, technologies such as Blockchain can be instrumental in the proper disposal and handling of wastes. In this paper, we propose a Blockchain-based Solid Waste Management (SWM) model that can help municipalities enhance the efficiency of their waste management efforts. A Blockchain framework owned and controlled by a municipality is proposed in which customer companies pay to join the platform to avail services from the suppliers managed by the municipality. The cost burdens to both supplier and consumer companies have been discussed. In addition, an optimization model is developed to determine the optimal quantity of waste that can be traded between supplier and consumer companies in order to maximize their profit based on parameters such as the number of suppliers, consumer companies, and the processing capacity of customer companies and several constraints including maximum storing capacity, storage, and transportation constraints. Further, the cost aspects associated with Blockchain implementation are estimated from several use cases obtained from companies providing Blockchain solutions.

Digital Transformation and Environmental Sustainability: A Review and Research Agenda

Digital transformation refers to the unprecedented disruptions in society, industry, and organizations stimulated by advances in digital technologies such as artificial intelligence, big data analytics, cloud computing, and the Internet of Things (IoT). Presently, there is a lack of studies to map digital transformation in the environmental sustainability domain. This paper identifies the disruptions driven by digital transformation in the environmental sustainability domain through a systematic literature review. The results present a framework that outlines the transformations in four key areas: pollution control, waste management, sustainable production, and urban sustainability. The transformations in each key area are divided into further sub-categories. This study proposes an agenda for future research in terms of organizational capabilities, performance, and digital transformation strategy regarding environmental sustainability.

The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal

Generation of healthcare waste from different patient care activities in hospitals, pathology labs and research centres has been a matter of great concern for environmental and social bodies across the world. This concern comes from its infectious and hazardous nature which brings life taking disease such as human immunodeficiency virus and Hepatitis-B. Moreover, with the outbreak of corona virus disease 2019 (COVID-19) pandemic across the world, healthcare waste has become even more infectious like never before and showing its potential for claiming lives if not disposed properly. Additionally, the COVID-19 has put up another challenge in terms of exponentially increasing demand for personal protective equipments for healthcare workers such as doctors, nurses, ward boys, and sanitation workers. In this paper, seven criteria related to smart healthcare waste disposal system infused by circular economy aspects to recover value from disposables are identified and analysed using a decision making trial and evaluation laboratory (DEMATEL) method. The criteria have been prioritized by its importance and net cause and effect relationship through a causal diagram. Two criteria, (i) digitally connected healthcare centres, waste disposal firms and pollution control board, and (ii) providing a pollution control board's feedback app to public and other stakeholders, feature as strong reasons for a smart healthcare waste disposal system. Conclusively, this study provides a causal relationship model among the intertwined drivers of industry 4.0 and circular economy for developing a smart healthcare waste disposal system enriched with the benefits of circular economy.

The importance of public support in the implementation of green transportation in smart cities using smart vehicle bicycle communication transport

Purpose

Smart mobility is a major guideline in the development of Smart Cities’ transport systems and management. The issue of transition into green, secure and sustainable transport modes, such as using bicycles, should be implemented in this case, along with the subjectivism of management.

Design/methodology/approach

The proposed technology reflects the Smart Bicycle vehicle model, which tracks cyclists and weather conditions and turns to electric motors in critical circumstances.

Findings

This reduces the physical load and battery consumption of cyclists which affects the Smart Cities’ ecology positively.

Originality/value

In Smart Vehicle Bicycle Communication Transport, the vehicle movement optimization technique is used for traffic scenarios to analyze traffic signaling systems that give better results in variable and dense traffic conditions.

Embedded systems and the Internet of Things: Can low-cost gas sensors be used in risk assessment of occupational exposure?

The Internet of Things (IoT) explores new perspectives and possible improvements in risk assessment practices and shows potential to measure long-term and real-time occupational exposure. This may be of value when monitoring gases with short-term maximum levels and for time-weighted average (TWA) concentrations used in standard measuring practices. A functional embedded system was designed using low-cost carbon monoxide (CO) electrochemical sensors and long-range-wide-area-network radio communication technology (LoRaWAN) was used to enable internet connectivity. This system was utilized to monitor gas levels continuously in the working atmosphere of an incineration plant over a 2-month period. The results show that stable and long-term continuous data transfer was enabled by LoRaWAN, which proved useful for detecting rapid changes in gas levels. However, it was observed that raw data from the low-cost sensors did not meet the NIOSH accuracy criteria of ± 25% of the estimated true concentration based on field data from a co-located gas detector that met the NIOSH accuracy criteria. The new IoT technologies and CO sensor networks shows potential for remote monitoring of exposure in order to: (1) detect rapid changes in CO and other possible hazardous airborne gases; and (2) show the dynamic range of real-time data that may be hazardous for workers in the sampled areas. While the IoT low-cost sensors appear to be useful as a sentinel for monitoring hazardous atmospheres containing CO, the more useful finding may be showing real-time changes and the dynamic range of exposures, thus shedding light on the transient and toxic nature of airborne hazards. More importantly, the low-cost CO sensors are not a clear substitute for the more costly real-time gas detectors that perform within the NIOSH accuracy criteria.

A review on the recycling processes of spent auto-catalysts: Towards the development of sustainable metallurgy

Spent auto-catalysts are considered as promising platinum group metals (PGMs) resources based on their rapidly increasing demand along with the underlying uncertainty of the sustainability and long-term availability of PGMs. Recycling spent auto-catalysts presents attractive advantages, particularly for the conservation of primary resources reserves, and for the reduction of negative environmental impact due to exploitation. PGM reclamation is the major aim of recycling operations despite their minor concentration in spent auto-catalysts, which implies that the remaining materials are disposed of as unwanted solid waste after the extraction process. This poses a genuine challenge, as well as a motivation to develop recycling processes for spent auto-catalysts capable of recovering all components/valuable metals, while moderating environmental pollution and global warming. The focus herein involves the description of the available technologies, including pyro- and hydro-metallurgical processes, to recover PGMs from spent auto-catalysts, and specifically an analysis of the developmental trends in recycling methods to ensure "sustainable metallurgy".

Analysis of Municipal Waste Development and Management in Self-Governing Regions of Slovakia

In the European Union, basic strategy results from the need to provide intelligent, sustainable, and inclusive growth, along with respect to social and economic impacts of waste treatment. The paper focuses on municipal waste and its separation. Generally, within global waste management initiatives, the main goal is to minimize the negative effects of waste on the environment, as well as to increase and optimize the sources’ efficiency in the waste economy. Research on municipal waste development and its separation was done in individual regions of Slovakia to find if socially weaker regions have worse waste treatment. The results were compared according to the waste development per inhabitant and per household, as well as through rate indexes, which are connected to relationships between waste, social, and economic indexes. The results confirmed research results from other countries that show that the volume of municipal waste is increasing due to increased living standards of inhabitants. However, on the other hand, waste separation rates also increased—mainly based on the legislative support.

Big Data Analytics in Australian Local Government

Australian governments at all three levels—local (council), state, and federal—are beginning to exploit the massive amounts of data they collect through sensors and recording systems. Their aim is to enable Australian communities to benefit from “smart city” initiatives by providing greater efficiencies in their operations and strategic planning. Increasing numbers of datasets are being made freely available to the public. These so-called big data are amenable to data science analysis techniques including machine learning. While there are many cases of data use at the federal and state level, local councils are not taking full advantage of their data for a variety of reasons. This paper reviews the status of open datasets of Australian local governments and reports progress being made in several student and other projects to develop open data web services using machine learning for smart cities.

High-Performance Flocculants for Purification: Solving the Problem of Waste Incineration Bottom Ash and Unpurified Water

The silicon-aluminum-iron flocculant (PAFSi) combines the most abundant resources of waste incineration bottom ash and unpurified water, being regarded as one of the most promising approaches toward water purification. Herein, in this research, waste incineration bottom ash was employed to produce a cost-effective and highly efficient flocculant. PAFSi with a particle size of 214 nm and a zeta potential of 8.63 mV reached the optimum performance using a dosage of 2 mL/50 mL at pH from 8 to 11. The results with the copolymer exhibited the following: (1) a good flocculation efficiency over a wide pH range, (2) superior flocculation performance compared to those of polyaluminum chloride and polyferric sulfate, (3) three-dimensional branching structure of PAFSi micelles with a high aggregation degree, (4) charge neutralization and bridging as the main flocculation mechanism, and (5) recycling the floc. Thus, this work provides an attractive solution to the pressing global clean water shortage problem.

Application of deep learning object classifier to improve e-waste collection planning

This study investigates an image recognition system for the identification and classification of waste electrical and electronic equipment from photos. Its main purpose is to facilitate information exchange regarding the waste to be collected from individuals or from waste collection points, thereby exploiting the wide acceptance and use of smartphones. To improve waste collection planning, individuals would photograph the waste item and upload the image to the waste collection company server, where it would be recognized and classified automatically. The proposed system can be operated on a server or through a mobile app. A novel method of classification and identification using neural networks is proposed for image analysis: a deep learning convolutional neural network (CNN) was applied to classify the type of e-waste, and a faster region-based convolutional neural network (R-CNN) was used to detect the category and size of the waste equipment in the images. The recognition and classification accuracy of the selected e-waste categories ranged from 90 to 97%. After the size and category of the waste is automatically recognized and classified from the uploaded images, e-waste collection companies can prepare a collection plan by assigning a sufficient number of vehicles and payload capacity for a specific e-waste project.

Immobilization mechanism of Se oxyanions in geopolymer: Effects of alkaline activators and calcined hydrotalcite additive

Geopolymers have been widely adopted to stabilize the cationic pollutants. However, few studies have focused on the immobilization of anionic species. In this study, the immobilization of SeO₃^2- and SeO₄^2- was explored for the first time using geopolymer activated by different alkaline solutions (NaOH and Na₂SiO₃) with and without calcined hydrotalcite (CHT), characterized by TCLP, XRD, FTIR, TG, NMR, XAFS, and N₂ adsorption-desorption isotherm. Na₂SiO₃-activated geopolymers without CHT additive showed lower leaching percentages of SeO₃^2- and SeO₄^2- (approximately 10 % and 18 %) than NaOH-activated geopolymers (approximately 58 % and 74 %). It has been proven that electrostatic interaction is the main association mode of SeO₃^2- and SeO₄^2- in both NaOH- and Na₂SiO₃-activated geopolymers. Hence, compactness plays a vital role in the Se leaching from geopolymer. The addition of CHT reduced the compactnesses of both NaOH- and Na₂SiO₃-geopolymers. Due to the formation of hydrotalcite, the CHT additive contributed to immobilize SeO₃^2- and SeO₄^2- in NaOH-activated geopolymers. However, this phenomenon was not observed in Na₂SiO₃-activated geopolymers. Thus, the leaching amount of Se greatly increased from Na₂SiO₃-activated geopolymers with CHT additive. This study provides new insights on the application of geopolymer to immobilize anionic pollutants.

Archetypical CBMs in Construction and a Translation to Industrialized Manufacture

The circular economy is a widely accepted concept that various governments have started to adopt. Still, a major consumer of resources, the construction industry, struggles to implement business models that answer to the opportunity and generate value beyond economical. At the same time, the industry is at a threshold of intensifying their production by industrialized manufacture. This type of construction offers practical benefits and should be developed whilst prioritizing a sustainably built environment. A circular economy business model (CBM) offers all stakeholders long term value and revenue whilst moving towards a sustainable environment. The business model canvas (BMC) is a tool to shed light on the essential characteristics of a CBM, its value, and alignment in a multi-life cycle perspective. It can contribute to accelerating circular innovation in construction. This study aims to provide an overview of archetypical CBMs in construction based on a literature review and a systematic coding exercise using the BMC. The archetypes found are used to describe the characteristics of industrialized manufacture in the various circular economy construction scenarios.