Waste Collection Process Research Articles

IoT-Aware Waste Management System Based on Cloud Services and Ultra-Low-Power RFID Sensor-Tags

Waste management is a challenge for modern cities as it impacts on environmental sustainability and on the level of quality perceived by citizens. In the last few years, several progresses have been made in this direction with the introduction in the city of door-to-door separate waste collection. A key element for the success of such actions is to achieve excellent cooperation from citizens. The Digital Transformation process in this sector will require time other than a careful management of the data associated with the waste collection processes. At this regard, the progress of hardware and software technologies enabling the Internet of Things (IoT) will contribute significantly to accelerate the whole process. Among these innovative solutions, the use of RFID tags with augmented capabilities and cloud-based software architectures capable of properly managing collected data will be crucial to obtain an intelligent and efficient waste management system. In this paper, an innovative system capable of capturing and processing data relating to the door-to-door separate waste collection in the context of future smart cities is presented. In particular, the system includes an innovative RFID sensor-tag equipped with low-cost weight sensors and a Cloud software system capable of managing the collected data and satisfying the various stakeholders' expectations. First results on both functional and performance validation of the overall system are shown.

Do E‐Waste Laws Create Behavioral Spillovers? Quasi‐Experimental Evidence from California

Many governing bodies have launched efforts to shape the operations of manufacturers, administration of civic entities, and behavior of individuals to limit waste generation. Typically, such efforts commence with the enactment of targeted legislations that create operational changes (e.g., recycling fees, collection centers) to the waste collection and disposal processes. For example, over 25 states in the United States have enacted legislations that aim to properly dispose used electronic and electrical goods (i.e., e‐waste) and divert such waste away from landfills. We argue that such legislations can have an impact that extends beyond just reducing e‐waste. This is because such laws may not only motivate individuals to restrict e‐waste but also induce broader behavioral spillovers that can prompt individuals to reduce waste in general. To explore this idea, we exploit a quasi‐experimental setup that arises from California's enactment of the Electronic Waste Recycling Act (EWRA). Specifically, a difference‐in‐differences analysis reveals that the introduction and implementation of the EWRA resulted in at least 4.93% reduction in municipal solid waste (MSW). A plausibility analysis illustrates that these MSW reductions are much larger than what can be attributed purely to the decline of e‐waste. Furthermore, we show that the effect of e‐waste laws is stronger when consumers have increased market access through (i) online connectivity and (ii) offline proximity. Our study informs policy makers on the effects of e‐waste legislation and the critical role of market access in enhancing the impact of such legislation.

A proposed sustainable and digital collection and classification center model to manage e-waste in emerging economies

PurposeThis study aims to propose an electronic waste collection and classification system to enhance social, environmental and economic sustainability by integrating data-driven technologies in emerging economies.Design/methodology/approachGM (1, 1) model under grey prediction is used in this study in order to estimate the trend of the amount of collected electronic waste in emerging economies.FindingsIt is revealed that the amount of collected electronic waste is increasing day by day, and within the framework of sustainability in the process of collecting and classification of electronic waste, digital technologies were found to be lacking. It has been determined that this deficiency, together with the increasing amount of electronic waste, has caused environmental, social and economic damage to emerging economies.Originality/valueThe main originality of this study is integrating electronic waste collection and classification processes with data-driven technologies and sustainability, which is a relatively new subject.

Towards a better environment - the municipal organic waste management in Brisbane: Environmental life cycle and cost perspective

Different options for treating organic fraction of municipal solid waste were assessed. Four composting scenarios were designed based on different scales (i.e. home vs centralised) and technologies (i.e. windrow vs in-vessel composting) in Brisbane. The environmental and economic performance were analysed and compared to the existing practice: landfilling, using life cycle assessment and life cycle costing analysis with the consideration of the costs of externalities and potential avoided costs. The treatment of 1 Mg of home organic waste was selected as one Functional Unit. The system boundaries start from waste collection to the use of the final product (i.e. compost). The compost was assumed to be applied on private gardens and tropical horticultural crops in home and centralised composting scenarios, respectively. Shared home composting bin in a small community (HC-II) presented the best overall performance from both environmental and economic perspectives, meanwhile, landfilling was found to be the worst option. The home composting scenarios require less energy which results in four times lower fossil depletion and human toxicity potential compared to centralised composting scenarios. However, the greenhouse gas (GHG) emissions released through organic waste degradation, due to potential partial anaerobic conditions, were identified as the major environmental impact factor, followed by the compost bin manufacturing. In both centralised composting scenarios, the energy consumption was found as the main environmental impact factor, which accounted for more than 45% of the total GHG emissions, followed by the waste collection and transportation process. Regarding the economic performance, the HC-II scenario has the lowest life cycle cost ($22.93/FU). Monte Carlo Analysis was carried out to test the effect of overall uncertainties. Our result showed that the compost application rate had the highest sensitivity in home composting scenarios because the unused compost would need to be collected and sent to the landfill. Consequently, extra transportation emissions and life cycle cost will incur, thus, the benefits from compost application will also be reduced. However, the overall uncertainties did not affect the ranking of the centralised (windrow) composting scenario, which remained the best environmental performer. Meanwhile, HC-II option had the better economic performance that marginally over-weighed the environmental performance of the centralised windrow composting; hence result in the best overall performer. However, in order to encourage residents to participate, enabling policies and incentives may be required to influence the behaviour of the independent households to share a composting bin.

The research on the characteristic of the cutting force while chipping of the Caucasian Fir (Abies Nordmanniana) with a single-shaft wood chipper

Waste management in a selective manner requires the collection of waste, among others, also large-scale. In Poland, in January and February, the collection of biodegradable waste is carried out – Christmas trees. This process is carried out by collecting from the real estate the whole trees, and then transporting them to the utilization place, where they undergo chipping processes. The article discusses the subject of estimating the cutting force when chipping a single-shaft wood chipper of the Caucasian Fir (Abies Nordmanniana). The obtained results of the loads characteristics and values of forces will enable the design of effective chipping machines. They can also help improve the efficiency of the selective waste collection process i.e. Christmas trees by developing mobile chipping machines mounted on waste collection vehicles. They will allow to limit the number of operations in the waste treatment process to collect and transport the shredded biodegradable mass to the processing stations.

Waste Segregation Using Smart Bin and Optimization of Collection Routes

Waste management is one of the crucial universal problems at present. The rapid growth in world population, their intricate living styles and the pace of urbanization has increased the amount of solid waste produced. Therefore, having a legitimate checking component is an absolute necessity to deal with the situation. India has policies to deal with all kinds of waste but implementation is weak and not monitored effectively. Plastics stay an issue of concern. Protests over strong waste dumping across India have increased. Our Objective is create a model which will be used to segregate and optimize waste management and collection process. The proposed system will sense different types of waste and segregate them at the user end and will inform the authority when the waste bins are getting filled. It will also provide users with a proper dumping technology to put their waste into the assigned bins and also guide them to the nearest bin if they encounter any problem with bins.

Cyber-physical System Enabled in Sustainable Waste Management 4.0: A Smart Waste Collection System for Indonesian Semi-Urban Cities

Cyber-physical System has become a trending topic undergoing intense discussion among industries, academicians, government, and communities globally to be implemented into critical infrastructures in a city, including waste management. In developed countries, cyber-physical system (CPS) is convinced to improve waste collection process, to reduce transportation energy and cost, to reduce labour and facilities inefficiency, to improve community health, and to create more value to the waste. However, the study of the CPS applied in waste management is still lacking from attention and very limited in Indonesia. This study has an objective to develop a smart waste collection system which integrates physical and cyber spaces to compute, to control and to communicate all waste management components including technology, facility, information, sensors, actuators, and networking. In-depth research on nonorganic waste banks management presents a task sharing platform of a waste collection system and a smart waste collection system using sensing platform suitable for semi-urban cities in a developing country. The model shows an integrated and connected element involved in waste collection management.

Assessment of the municipal waste collection process on the basis of irregularities notifications sent by residents – A case study in Wroclaw, Poland

Assessment of the municipal waste collection process on the basis of irregularities notifications sent by residents – A case study in Wroclaw, Poland

Optimasi Rute Pengangkutan Sampah Kota Yogyakarta Menggunakan Hybrid Genetic Algorithm

The increasing population in Yogyakarta City has implications for consumption and solid waste production activities. The waste collection process is the most expensive one in municipal waste management. It is necessary to determine the optimal route for municipal waste collection. In this research, we developed a vehicle routing problem (VRP) with a heterogeneous fleet, multiple trips, intermediate facility, and split delivery to approach the Yogyakarta City waste collection problem. We proposed a hybrid genetic algorithm (GA) to solve the VRP. The result of this study shows that developed VRP can be used to solve the Yogyakarta City waste collection problem.

Optimization analysis of route determination and trash distribution policy in Garut City

This study sought a solution to the problem of garbage collection and finding the optimal garbage distribution route starting from the Temporary Waste Disposal Site (TPS) to the Final Disposal Site (TPA) using available vehicles based on the capacity spread in each polling station. This study proposes an optimization formulation to model VRP; shipping is divided into several locations to determine the minimum distance route. The first stage optimally determines the transient trash collection points that cover all aspects of the city area. The second stage applies the Saving Matrix method, where this method is used to find the distance from each destination by minimizing the length taken in the process of distributing waste from each polling station to the final destination of the landfill. This research contributes to modelling the VRP in current conditions and introducing heuristic methods to solve problems efficiently. This study is significant to do to apply the basis for understanding the possibility of increasing service levels in the distribution process of the municipal waste collection.

Influence of the Municipal Solid Waste Collection System on the Time Spent at a Collection Point: A Case Study

Waste management plans pay attention to municipal solid waste (MSW) collection systems. It represents a significant portion of waste management as it involves a great economic cost and environmental impact. For these reasons, many researchers have studied the optimization of collection routes, analyzing factors that make them more efficient and sustainable, for example, the overall distance traveled and the time spent on the route. Collection times depend on factors such as the speed of the truck, time at traffic lights or time spent on loading and unloading the waste. The loading and unloading times play an important role in the measurement of the total time of the route. Moreover, there is scarce information in the literature about measuring the real-time spent on the trip. All those times are necessary to optimize the total route time. However, it is difficult to obtain this information directly as it depends on parameters such as the type of truck. The aim of this work is to propose a methodology to define all the times involved in the waste collection process. Once they are well defined, they have to be measured in some cases or calculated in others. This works also presents a case study to validate the proposed methodology with an extensive fieldwork to measure those times that can’t be calculated in the waste collection process. The work presents the results of a study of the time spent at a collection point in six MSW collection systems using different types of collection trucks and bin designs. We have determined how the characteristics of the system affect the time spent at a collection point. Additionally, the times for the six models have been established. Finally, we have determined the influence of the collection model in the duration of the activity. Under certain conditions, times can coincide even though the models are different.

A fuzzy optimization approach to the capacitated node-routing problem for municipal solid waste collection with multiple tours: A case study.

In many countries, municipal solid waste management is considered a very important challenge, and the most relevant costs in this field are dedicated to the collection process. Therefore, this study aimed to propose a mathematical model with multiple depots and multiple intermediate facilities to minimize fixed and variable costs of waste collection. Intermediate facilities are used in the developed countries in their waste collection network, because these facilities reduce the long-term costs of waste management and increase the quality of the waste collection process. Also, in reality, the amount of waste generated per day is not deterministic, so, to cope with the issue of uncertainty in the amount of waste, a fuzzy optimization approach was considered. Furthermore, a system where vehicles that could collect the wastes in multiple tours, with a maximum number of tours for each vehicle, was also considered. Due to the high complexity of this model, a genetic algorithm was elaborated. Further, the efficiency of the proposed algorithm was confirmed by comparison with the exact solution in small dimensions. It should be noted that the initial solution of this algorithm was obtained by a proposed heuristic algorithm. Finally, a case study on the vehicle routing of municipal solid waste was conducted in a district of Tehran, Iran. Moreover, the solutions of the model were validated by comparing the results of the proposed model and the current real-life situation. The contractors could improve vehicle routes and reduce costs by implementing the results of the proposed model, without any additional cost.

Optimal Management of Solid Waste in Smart Cities using Internet of Things

Smart cities are benefiting from Internet of Things (IoT) in optimizing their services. Smart waste management systems can provide substantial savings in time, monetary cost, trip length and utilization of vehicles. In this paper, we use the IoT technology to determine the schedule and pathways of waste collection trucks. We discuss our previous work on single truck routing algorithm and develop and simulate two-step heuristic algorithm multiple trucks routing algorithm (MITRA) to discover the ideal route for the management waste fleet, using smart dumpsters and agent-based models. The smart dumpsters are equipped with the sensors that measure levels of waste and a controller to send updates to the central management system using wireless network. Our target is to improve the waste collection process by reducing the congestion on the road, the service time spent and the overall trip length. We developed the MITRA algorithm applying the timing constraint on capacitated vehicle routing problem. MITRA divides the metropolitan area into a set of sectors each containing a number of dumpsters. We guide the routing in waste collection by selecting the order of sectors to be served then then apply genetic algorithm to compute the optimal route to serve the full dumpsters in the sector.

Household Waste Management Policy and Practices in Bengaluru

Households play a very important role in waste management policy development and its implementation in any city. This study is done among households of 12 wards in Urban Bengaluru(India). It is observed that waste management is open of the most important issue among households and households in general are not satisfied by waste collection, segregation its transport service and maintenance of public places, provided by local municipal body. Garrett's ranking method is also used to give ranking for various waste management practices adopted by various wards. The results suggest that problems faced by households across the city is not same, also perception towards the policy and practices of local bodies towards waste management differs significantly across the city. Cleanliness of public places and waste collection process should be given highest priority by the policy makers. The study also determines a different perspective towards understanding behaviour of household. the policymakers may use this technique to identify specific geographic areas where immediate action is required.

Route optimization of an electric garbage truck fleet for sustainable environmental and energy management

The waste collection process is an issue where numerous studies have already been conducted in the existing literature especially based on finding the optimal routes for the garbage trucks assigned in this service process. In this manner, A Mixed-Integer Linear Programming (MILP) based route optimization model has been conducted as the first attempt for waste collection-oriented electric garbage trucks routing process in this study. Even different studies exist in the literature for the route optimization of conventional fuels-based garbage trucks as mentioned above, no studies devote to considering the electric garbage trucks to the best of our knowledge. Besides, it is not easy to reach the detailed garbage collection area information in the literature. In this manner, data have been obtained by real field measurements in a region within the service area of Bakirkoy Municipality, Istanbul, Turkey. A unit energy consumption value that can be considered as a reference in the future has also been obtained using real data. Besides, real road information data have been integrated to the data used as input while assessing the optimization approach and the system analyses have been conducted in a more realistic concept. The proposed concept has led to an increased reality of nearly 38% for the analysis of the results under conditions closer to real-time, and a decrement of nearly 32% has been obtained. It is expected that this study may lead a conceptual input to an enhanced and greener waste collection process.

Psychological and physical job demands, decision latitude, and work-related social support among Iranian waste collectors

Waste collection is known as a stressful and physically demanding job in low/middle income countries. This study aimed to assess the psychological and physical job demands, decision latitude, and work-related social support among Iranian waste collectors. In this cross-sectional study, field observation, video capture, and unstructured interviews were performed to understand the process of waste collection. Data were collected from 200 waste collectors of Shiraz city using a demographic/work characteristics questionnaire and a job content questionnaire (JCQ). Logistic regression analysis was used for the prediction of independent variables affecting job content dimensions. A p < 0.05 was considered to be statistically significant. Results show that the rate of municipal solid waste (MSW) generation in Shiraz city was 0.576 kg/capita/day, which translates into about 1076 tons of waste per day per the current population of 1,869,001. The total amount of MSW produced in Shiraz over a four-year period from 2014 to 2017 were 346,093, 363,505, 392,869, and 400,863 tons, respectively. About half of the waste collectors reported high levels of psychological and physical job demands. More than half were concerned with the low level of decision latitude and social support in the workplace. Night-workers (OR = 3.29) and smokers (OR = 2.75) reported higher psychological job demands than day-workers and non-smokers, respectively. Decision latitude and social support were inversely associated with the level of education (OR = 1.90), and daily working time (OR = 2.46), respectively. Based on the Demand-Control-Support Model, waste collectors were exposed to relatively high levels of job stress associated with occupational risk factors.

Design of Medical Wastes Incinerator for Health Care Facilities in Akure

Health Care Facilities (HCFs) are primarily saddled with the responsibilities of providing medical care, thus ensuring sound health of individuals. Tremendous efforts have been made by the government to ensure her availability in nooks and crannies of every community, which have resulted into improved medical services. However, among other environmental challenges confronting health care facilities in developing countries is Medical Waste generated in the course of carrying out their duties which is often ignored and in most instances treated as municipal or domestic solid waste. Effective management of medical waste requires keen planning, training and tracking throughout the waste generation, segregation, storage, collection, transportation, treatment and disposal processes. The fundamental information for selecting and designing the most efficient treatment method of medical waste is obtained by means of Waste Composition Analysis. Results from this study revealed that the daily waste generation rate of Ondo State Specialist Hospital Akure (OSSHA) and Mother and Child Hospital Akure (MCHA) was 124.5 kg/day. The hospitals’ waste consists of 81.6% combustible wastes and 18.4% non-combustible wastes by mass. The combustible wastes are paper (6.50%), textiles (14.34%), cardboard (3.88%), plastics (6.04%) and food waste (19.08%). Since the ratio of combustible medical waste is higher than non-combustible medical waste, incineration (thermal destruction) at elevated temperature under controlled operational condition is considered the best disposal option to detoxify the medical waste. In other to prevent the release of harmful gases from burnt medical waste through incinerator, a counter-current packed bed wet scrubber is designed which operates by impaction and absorption.

BIN-CT: Urban waste collection based on predicting the container fill level

The fast demographic growth, together with the population concentration in cities and the increasing amount of daily waste, are factors that are pushing to the limit the ability of waste assimilation by Nature. Therefore, we need technological means to optimally manage of the waste collection process, which represents 70% of the operational cost in waste treatment. In this article, we present a free intelligent software system called BIN-CT (BIN for the CiTy), based on computational learning algorithms, which plans the best routes for waste collection supported by past (historical) and future (predictions) data.The objective of the system is to reduction the cost of the waste collection service minimizing the distance traveled by a truck to collect the waste from a container, thereby reducing the fuel consumption. At the same time the quality of service for the citizen is increased, avoiding the annoying overflows of containers thanks to the accurate fill-level predictions given by BIN-CT. In this article we show the features of our software system, illustrating its operation with a real case study of a Spanish city. We conclude that the use of BIN-CT avoids unnecessary trips to containers, reduces the distance traveled to collect a container by 20%, and generates routes 33.2% shorter than the routes used by the company. Therefore it enables a considerable reduction of total costs and harmful emissions thrown up into the atmosphere.

Optimization of Municipal Waste Collection Routing: Impact of Industry 4.0 Technologies on Environmental Awareness and Sustainability.

The accelerated movement of people towards cities led to the fact that the world’s urban population is now growing by 60-million persons per year. The increased number of cities’ population has a significant impact on the produced volume of household waste, which must be collected and recycled in time. The collection of household waste, especially in downtown areas, has a wide range of challenges; the collection system must be reliable, flexible, cost efficient, and green. Within the frame of this paper, the authors describe the application possibilities of Industry 4.0 technologies in waste collection solutions and the optimization potential in their processes. After a systematic literature review, this paper introduces the waste collection process of downtowns as a cyber-physical system. A mathematical model of this waste collection process is described, which incorporates routing, assignment, and scheduling problems. The objectives of the model are the followings: (1) optimal assignment of waste sources to garbage trucks; (2) scheduling of the waste collection through routing of each garbage truck to minimize the total operation cost, increase reliability while comprehensive environmental indicators that have great impact on public health are to be taken into consideration. Next, a binary bat algorithm is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and then evaluates its performance to increase the cost-efficiency and warrant environmental awareness of waste collection process.

An artificial bee colony-based hybrid approach for waste collection problem with midway disposal pattern

This paper investigates a waste collection problem with the consideration of midway disposal pattern. An artificial bee colony (ABC)-based hybrid approach is developed to handle this problem, in which the hybrid ABC algorithm is proposed to generate the better optimum-seeking performance while a heuristic procedure is proposed to select the disposal trip dynamically and calculate the carbon emissions in waste collection process. The effectiveness of the proposed approach is validated by numerical experiments. Experimental results show that the proposed hybrid approach can solve the investigated problem effectively. The proposed hybrid ABC algorithm exhibits a better optimum-seeking performance than four popular metaheuristics, namely a genetic algorithm, a particle swarm optimization algorithm, an enhanced ABC algorithm and a hybrid particle swarm optimization algorithm. It is also found that the midway disposal pattern should be used in practice because it reduces the carbon emission at most 7.16% for the investigated instances.