Search Results (8)

As global waste production continues to rise, improper handling of household waste significantly contributes to environmental pollution and resource depletion. Inefficient sorting at the household level leads to the contamination of recyclables, reducing recycling efficiency and increasing landfill waste. Effective waste sorting is essential for conserving manual labor, protecting the environment, and ensuring sustainable development for human progress. Recently, advancements in deep learning and computer vision have offered a promising pathway to improve the sorting process, though significant developmental steps are still required. Enhancing the efficiency of automated waste detection and classification through computer vision could bring substantial societal and environmental benefits. However, classifying and identifying waste materials presents challenges due to the complex and diverse nature of waste, coupled with the limited availability of data on waste management. This paper presents a real-time waste detection and classification system based on the YOLOv8 deep learning model, designed to enhance waste sorting processes at the household level. The proposed system detects and classifies a diverse range of household waste items. Experiments were conducted on a custom waste dataset comprising 3775 images across 17 types of common household waste. The one-stage YOLOv8 model demonstrated superior performance, outperforming traditional two-stage detectors. To improve the accuracy and robustness of the original YOLOv8, five data augmentation techniques and two attention mechanisms were incorporated. Notably, the enhanced YOLOv8-CBAM model achieved a mean average precision (mAP) of 89.5%, a significant improvement with a 4.2% increase over the baseline model. The methodology and improvements applied provide a more efficient and effective AI framework for real-time applications in smart bins, robotic waste pickers, and large-scale recycling systems. Full article

Household waste is the primary source of environmental pollution due to global population growth compared to other waste sources. This article aims to develop a framework for a smart and integrated household waste management system through a Systematic Literature Review (SLR) using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA). The resulting framework not only focuses on information technology dimensions but also links them with other integrated dimensions. The framework’s design identifies the types of household waste management processes based on the Integrated Sustainable Waste Management (ISWM) framework, dimensions that support smart household waste management system, and the stakeholders involved. The SLR results, which include dimensions and subdimensions supporting the smart and integrated household waste management system framework, were validated by experts from the Indonesian Ministry of Environment and Forestry. The developed framework includes five main dimensions: Information Technology, Operational Infrastructure, Governance, Economy, and Social–Culture. It also addresses stakeholder engagement to support smart household waste management systems and identifies waste management processes based on the ISWM framework. This research uses the PRISMA technique to provide an initial framework for smart and integrated household waste management system. The proposed framework has been validated and can be further developed as a smart and integrated household waste management system. Additionally, it highlights the involvement of various dimensions identified to address waste problems. Full article

Food waste management remains a paramount issue in the field of social innovation. While government-led public recycling measures are important, the untapped role of residents in food waste management at the household level also demands attention. This study aims to propose the design of a smart system that leverages sensors, mobile terminals, and cloud data services to facilitate food waste reduction. Unlike conventional solutions that rely on mechanical and biological technologies, the proposed system adopts a user-centric approach. By integrating the analytical hierarchy process and the theory of inventive problem solving, this study delves into users’ actual needs and explores intelligent solutions that are alternatives to traditional approaches to address conflicts in the problem solving phase. The study identifies five main criteria for user demands and highlights user-preferred subcriteria. It determines two physical conflicts and two technical conflicts and explores corresponding information and communications technology (ICT)-related solutions. The tangible outcomes encompass a semi-automated recycling product, a mobile application, and a data centre, which are all designed to help residents navigate the challenges regarding food waste resource utilisation. This study provides an approach that considers users’ genuine demands, empowering them to actively engage in and become practitioners of household food waste reduction. The findings serve as valuable references for similar smart home management systems, providing insights to guide future developments. Full article

Due to rapid urbanization, solid waste management (SWM) is a major challenge in Malaysia, hence the need to sustainably manage it. Compared with other states, Selangor produces the highest volume of domestic waste. Most of the state’s waste is generated in Shah Alam City. This condition is expected to worsen because the population of Shah Alam is projected to rise by 2.5% from 2018 to 2035. This situation will increase the demand for resources, production, and consumption, increasing the volume of waste generated in Shah Alam. Hence, the pressing necessity to advance from the current traditional waste management practices to a more sustainable SWM system has been identified as a key target in Shah Alam’s 2025–2030 plans. The Smart Waste Management System (SWMS) has been identified as a novel approach to dealing with the absence of route optimization, real-time information exchange, and the consequent increase in waste management costs. All of these elements have characterized the current traditional households’ SWM. However, because this method is novel, there is a dearth of knowledge on the appropriate measurement model for evaluating the dimension of households’ intention to recycle waste through source separation as well as measuring the determinants of such a pro-environmental intention under the new SWMS. Thus, confirmatory factor analysis (CFA) was carried out to verify the factorial structure of the variables, relying on the Theory of Planned Behavior (TPB) based on the structural dimensions identified in prior exploratory factor analysis (EFA). The study found support for the use of TPB as a relevant framework for modeling the intention for source separation and its determinants under SWMS. Full article

This article introduces a Smart and Sustainable Societies (S³) framework, based on what is necessary to achieve the UN agenda by 2030. The proposed model is based on the integration of three smart strategies: (1) water provision that consists of the use of greywater and rainwater; (2) sanitation provision that comprises the nutrients recovery from excreta and organic solid waste and; (3) resource-oriented agriculture that conceives the use of the water provision system for the production of food with the use of nutrients recovered from the sanitation system. The S³ framework has the potential to increase the well-being, human development, water availability, food safety, poverty alleviation, and healthy environments of societies through the provision of safely managed basic services as well as the recycling of nutrients and water to achieve sustainability at household and community levels. Full article

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

The increase of source-separation of bio-waste, largely represented by food waste, and their subsequent biological treatment, is essential in waste management strategy. Aerobic and biological composting of bio-waste is a process that requires experience and technical skills, thus backyard composting can be a challenging task for the average household, with failed attempts often leading to its abandonment. Here we present the development of an integrated system including a low-cost sensor, a smart phone application, and a cloud-based service that can assist in backyard composting. The system builds on the composting-as-a-service concept. Installed in a waterproof capsule, the sensor monitors temperature at the core of the compost pile and transmits the readings to a smartphone application using Bluetooth Low Energy (BLE) technology. Based on compost temperature readings and a data feed of environmental parameters, a cloud-based service provides insight on the status of the composting process and advice for manual intervention. By supplying timely information for compost pile management, the system can increase the potential for producing a high-quality compost soil amendment and therefore the probability that backyard composting is adopted by the user. In the context of the backyard composting activity of the UIA A2UFood Project, the system is tested in a community of 100 households in Heraklion, Crete, and preliminary results are presented. Full article

Municipal solid waste management is one of the major challenges that cities in developing countries are facing. Although waste collection services are critical to build a smart city, the focus of both scholarship and action/activism has been more on the utilization of waste than on collection. We devised a choice experiment to elicit the preferences of municipal residents with regard to the various attributes of solid waste collection services in the Bharatpur Metropolitan City of Nepal. The study showed that households identify waste collection frequency, timing of door-to-door waste collection services, and cleanliness of the streets as the critical elements of municipal waste collection that affect their welfare and willingness to pay. While almost all households (95%) were participating in the waste collection service in the study area, more than half (53%) expressed dissatisfaction with the existing service. Women were the main actors engaged in waste collection and disposal at household level. The results of the choice analysis suggest that households prefer a designated waste collection time with waste collection bins placed at regular intervals on the streets for use by pedestrians who often throw garbage on the streets in the absence of bins. For these improvements, households were willing to pay an additional service fee of 10–28% on top of what they were already paying. The study also finds that municipal waste collection can be improved through the involvement of Tole Lane Committees in designing the timing and frequency of the service and by introducing a system of progressive tariffs based on the number of storeys per house. Full article