Sensorized waste collection container for content estimation and collection optimization

Volume Determination Challenges in Waste Sorting Facilities: Observations and Strategies

In this case study on volume determination in waste sorting facilities, we evaluate the effectiveness of ultrasonic sensors and address waste-material-specific challenges. Although ultrasonic sensors offer a cost-effective automation solution, their accuracy is affected by irregular waste shapes, varied compositions, and environmental factors. Notable inconsistencies in volume measurements between storage bunkers and conveyor belts underscore the need for a comprehensive approach to standardize bale production. With prediction reliability being constrained by limited datasets, undocumented modifications to machine settings, and sensor failures, this task renders a challenging application area for machine learning. We explore related research and present dataset analyses from three distinct waste sorting facilities in Europe, addressing issues such as sensor usability, data quality, and material specifics. Our analysis suggests promising strategies and future directions for enhancing waste volume measurement accuracy, ultimately aiming to advance sustainable waste management.

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.

Open source IoT-based collection bin applied to local plastic recycling

Plastic waste is a major challenge for policy making; it has a terrible impact on the environment if it is not properly managed. In order to mitigate this issue, recycling industries have emerged with the associated logistics chain that also has an environmental impact, notably with the production of greenhouse gas. In addition to using energy to transform plastic waste into source material, energy is also wasted to transport it. In parallel to reducing plastic waste, it may be recycled at a very local scale, reducing transportation and allowing potential improvement of the collecting process. Assuming that local transformation of plastic waste is possible, this article describes the design, assembly, and setup of the hardware, system architecture, and software of collectors that may be used by these recycling units. The specificity of these collectors is that they produces on-line data related to the quantity of waste collected. Once implemented, a network of smart collectors should allow the reduction of travel to collect waste as it notifies when the collectors are full. It also produces data on the scale of a territory to optimize the supply chain related to plastic waste collection. This article presents the design and engineering aspects as well as limitations induced by technical choices, but also potential improvements for future developments.

Sensor-Based Solid Waste Handling Systems: A Survey

As a consequence of swiftly growing populations in the urban areas, larger quantities of solid waste also form rapidly. Since urban local bodies are found to be unable to manage this perilous situation effectively, there is a high probability of risks relative to the environment and public health. A sudden change is indispensable in the existing systems that are developed for the collection, transportation, and disposal of solid waste, which are entangled in turmoil. However, Smart sensors and wireless technology enable cyber-physical systems to automate solid waste management, which will revolutionize the industry. This work presents a comprehensive study on the evolution of automation approaches in solid waste management systems. This study is enhanced by dissecting the available literature in solid waste management with Radio Frequency Identification (RFID), Wireless Sensor Networks (WSN), and Internet of Things (IoT)-based approaches and analyzing each category with a typical architecture, respectively. In addition, various communication technologies adopted in the aforementioned categories are critically analyzed to identify the best choice for the deployment of trash bins. From the survey, it is inferred that IoT-based systems are superior to other design approaches, and LoRaWAN is identified as the preferred communication protocol for the automation of solid waste handling systems in urban areas. Furthermore, the critical open research issues on state-of-the-art solid waste handling systems are identified and future directions to address the same topic are suggested.

Indicators and ICTs application for municipal waste management

The worldwide populace is rising steadily. Urbanization is likewise expanding quickly with the rising populace. Fast urbanization has considerably increased the generation of municipal solid waste (MSW). The MSW management issues have recently been analyzed through various assessment indicators and information and communication technologies (ICTs). This article provides an overview of applications of assessment indicators and ICTs for addressing the environmental issues of waste disposal and management in municipalities. The selection of indicators mainly depends on the stakeholders' specific requirements, such as waste management strategies, urban planning and development, human health, and energy generation. The literature analysis revealed that collection, sorting, recycling, cost efficiency, and environmental aspect were the leading indicators used in waste management studies. And these indicators reduce the complexity of systems and formulate evaluations easier for the decision-maker. Moreover, these are also helpful in assessing the improvement and reporting the waste condition to the expert. These analysis further revealed that information and communication technology is a requirement in the planning and managing of current solid waste disposal problems. The use of ICTs in waste management systems mitigates possible constraints regarding spot selection, inept waste disposal, waste collection monitoring, and proper recycling.

A review on integrated approaches for municipal solid waste for environmental and economical relevance: Monitoring tools, technologies, and strategic innovations

Rapid population growth, combined with increased industrialization, has exacerbated the issue of solid waste management. Poor management of municipal solid waste (MSW) not only has detrimental environmental consequences but also puts public health at risk and introduces several other socioeconomic problems. Many developing countries are grappling with the problem of safe disposing of large amounts of produced municipal solid waste. Unmanaged municipal solid waste pollutes the environment, so its use as a potential renewable energy source would aid in meeting both increased energy needs and waste management. This review investigates emerging strategies and monitoring tools for municipal solid waste management. Waste monitoring using high-end technologies and energy recovery from MSW has been discussed. It comprehensively covers environmental and economic relevance of waste management technologies based on innovations achieved through the integration of approaches.

Remote sensing and GIS applications for municipal waste management

The production of municipal solid waste has increased noticeably during the recent past due to the mounting global population and fast urbanization. Furthermore, its poor management and inappropriate disposal are a global challenge since these have created environmental problems in urban ecosystems. Waste management problems are significantly stalled because of a lack of quality data. This is particularly the case in developing countries where observation infrastructure is weak. Regional waste management strategies involve distributed data, while typical small-scale studies present just point information and in the lack of vital widespread information, the regional studies can't provide dependable results. With the materialization of new techniques such as remote sensing and GIS, regional waste management studies have become easier during the last few decades. Use of these techniques in solid waste management supports in capturing, handling, and transmitting the required information in a prompt and proper manner. These techniques are also useful in acquiring information directly from the remote site at a fairly low cost. This paper provides an overview of remote sensing and GIS techniques used for managing the environmental problems of waste disposal. An indication of the waste disposal problems and its management alongside the ramifications of the analysis is discussed. The background and rationale of the waste disposal problems are detailed. The applications of remote sensing and GIS in waste management modeling are presented and applications of these techniques in diverse case studies worldwide are described. The study revealed that the efficiency of waste management system can be maximized by the proper use of remote sensing and GIS techniques. The study also revealed that these techniques were most commonly used for siting the landfill and waste bin for waste disposal and evaluation of environmental impact of buried waste.

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

The potential of smart cities in remediating environmental problems in general and waste management, in particular, is an important question that needs to be investigated in academic research. Built on an integrative review of the literature, this study offers insights into the potential of smart cities and connected communities in facilitating waste management efforts. Shortcomings of existing waste management practices are highlighted and a conceptual framework for a centralized waste management system is proposed, where three interconnected elements are discussed: (1) an infrastructure for proper collection of product lifecycle data to facilitate full visibility throughout the entire lifespan of a product, (2) a set of new business models relied on product lifecycle data to prevent waste generation, and (3) an intelligent sensor-based infrastructure for proper upstream waste separation and on-time collection. The proposed framework highlights the value of product lifecycle data in reducing waste and enhancing waste recovery and the need for connecting waste management practices to the whole product life-cycle. An example of the use of tracking and data sharing technologies for investigating the waste management issues has been discussed. Finally, the success factors for implementing the proposed framework and some thoughts on future research directions have been discussed.

Waste level detection and HMM based collection scheduling of multiple bins

In this paper, an image-based waste collection scheduling involving a node with three waste bins is considered. First, the system locates the three bins and determines the waste level of each bin using four Laws Masks and a set of Support Vector Machine (SVM) classifiers. Next, a Hidden Markov Model (HMM) is used to decide on the number of days remaining before waste is collected from the node. This decision is based on the HMM's previous state and current observations. The HMM waste collection scheduling seeks to maximize the number of days between collection visits while preventing waste contamination due to late collection. The proposed system was trained using 100 training images and then tested on 100 test images. Each test image contains three bins that might be shifted, rotated, occluded or toppled over. The upright bins could be empty, partially full or full of garbage of various shapes and sizes. The method achieves bin detection, waste level classification and collection day scheduling rates of 100%, 99.8% and 100% respectively.

A stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable cities

The concept of City 2.0 or smart city is offering new opportunities for handling waste management practices. The existing studies have started addressing waste management problems in smart cities mainly by focusing on the design of new sensor-based Internet of Things (IoT) technologies, and optimizing the routes for waste collection trucks with the aim of minimizing operational costs, energy consumption and transportation pollution emissions. In this study, the importance of value recovery from trash bins is highlighted. A stochastic optimization model based on chance-constrained programming is developed to optimize the planning of waste collection operations. The objective of the proposed optimization model is to minimize the total transportation cost while maximizing the recovery of value still embedded in waste bins. The value of collected waste is modeled as an uncertain parameter to reflect the uncertain value that can be recovered from each trash bin due to the uncertain condition and quality of waste. The application of the proposed model is shown by using a numerical example. The study opens new venues for incorporating the value recovery aspect into waste collection planning and development of new data acquisition technologies that enable municipalities to monitor the mix of recyclables embedded in individual trash bins.

Designing Pay-As-You-Throw schemes in municipal waste management services: A holistic approach

Pay-As-You-Throw (PAYT) strategies are becoming widely applied in solid waste management systems; the main purpose is to support a more sustainable - from economic, environmental and social points of view - management of waste flows. Adopting PAYT charging models increases the complexity level of the waste management service as new organizational issues have to be evaluated compared to flat charging models. In addition, innovative technological solutions could also be adopted to increase the overall efficiency of the service. Unit pricing, user identification and waste measurement represent the three most important processes to be defined in a PAYT system. The paper proposes a holistic framework to support an effective design and management process. The framework defines most critical processes and effective organizational and technological solutions for supporting waste managers as well as researchers.

A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges

In the backdrop of prompt advancement, information and communication technology (ICT) has become an inevitable part to plan and design of modern solid waste management (SWM) systems. This study presents a critical review of the existing ICTs and their usage in SWM systems to unfold the issues and challenges towards using integrated technologies based system. To plan, monitor, collect and manage solid waste, the ICTs are divided into four categories such as spatial technologies, identification technologies, data acquisition technologies and data communication technologies. The ICT based SWM systems classified in this paper are based on the first three technologies while the forth one is employed by almost every systems. This review may guide the reader about the basics of available ICTs and their application in SWM to facilitate the search for planning and design of a sustainable new system.

Inventory routing for dynamic waste collection

We consider the problem of collecting waste from sensor equipped underground containers. These sensors enable the use of a dynamic collection policy. The problem, which is known as a reverse inventory routing problem, involves decisions regarding routing and container selection. In more dense networks, the latter becomes more important. To cope with uncertainty in deposit volumes and with fluctuations due to daily and seasonal effects, we need an anticipatory policy that balances the workload over time. We propose a relatively simple heuristic consisting of several tunable parameters depending on the day of the week. We tune the parameters of this policy using optimal learning techniques combined with simulation. We illustrate our approach using a real life problem instance of a waste collection company, located in The Netherlands, and perform experiments on several other instances. For our case study, we show that costs savings up to 40% are possible by optimizing the parameters.

Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier

The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.

An automated solid waste bin level detection system using a gray level aura matrix

An advanced image processing approach integrated with communication technologies and a camera for waste bin level detection has been presented. The proposed system is developed to address environmental concerns associated with waste bins and the variety of waste being disposed in them. A gray level aura matrix (GLAM) approach is proposed to extract the bin image texture. GLAM parameters, such as neighboring systems, are investigated to determine their optimal values. To evaluate the performance of the system, the extracted image is trained and tested using multi-layer perceptions (MLPs) and K-nearest neighbor (KNN) classifiers. The results have shown that the accuracy of bin level classification reach acceptable performance levels for class and grade classification with rates of 98.98% and 90.19% using the MLP classifier and 96.91% and 89.14% using the KNN classifier, respectively. The results demonstrated that the system performance is robust and can be applied to a variety of waste and waste bin level detection under various conditions.

Pneumatic vs. door-to-door waste collection systems in existing urban areas: a comparison of economic performance

Pneumatic waste collection systems are becoming increasingly popular in new urban residential areas, and an attractive alternative to conventional vehicle-operated municipal solid waste (MSW) collection also in ready-built urban areas. How well pneumatic systems perform in ready-built areas is, however, an unexplored topic. In this paper, we analyze how a hypothetical stationary pneumatic waste collection system compares economically to a traditional vehicle-operated door-to-door collection system in an existing, densely populated urban area. Both pneumatic and door-to-door collection systems face disadvantages in such areas. While buildings and fixed city infrastructure increase the installation costs of a pneumatic system in existing residential areas, the limited space for waste transportation vehicles and containers cause problems for vehicle-operated waste collection systems. The method used for analyzing the cost effects of the compared waste collection systems in our case study takes into account also monetized environmental effects of both waste collection systems. As a result, we find that the door-to-door collection system is economically almost six times more superior. The dominant cost factor in the analysis is the large investment cost of the pneumatic system. The economic value of land is an important variable, as it is able to reverse the results, if the value of land saved with a pneumatic system is sufficiently high.

Solid waste bin level detection using gray level co-occurrence matrix feature extraction approach

This paper presents solid waste bin level detection and classification using gray level co-occurrence matrix (GLCM) feature extraction methods. GLCM parameters, such as displacement, d, quantization, G, and the number of textural features, are investigated to determine the best parameter values of the bin images. The parameter values and number of texture features are used to form the GLCM database. The most appropriate features collected from the GLCM are then used as inputs to the multi-layer perceptron (MLP) and the K-nearest neighbor (KNN) classifiers for bin image classification and grading. The classification and grading performance for DB1, DB2 and DB3 features were selected with both MLP and KNN classifiers. The results demonstrated that the KNN classifier, at KNN = 3, d = 1 and maximum G values, performs better than using the MLP classifier with the same database. Based on the results, this method has the potential to be used in solid waste bin level classification and grading to provide a robust solution for solid waste bin level detection, monitoring and management.

Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system

This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.

Integrated technologies for solid waste bin monitoring system

The integration of communication technologies such as radio frequency identification (RFID), global positioning system (GPS), general packet radio system (GPRS), and geographic information system (GIS) with a camera are constructed for solid waste monitoring system. The aim is to improve the way of responding to customer's inquiry and emergency cases and estimate the solid waste amount without any involvement of the truck driver. The proposed system consists of RFID tag mounted on the bin, RFID reader as in truck, GPRS/GSM as web server, and GIS as map server, database server, and control server. The tracking devices mounted in the trucks collect location information in real time via the GPS. This information is transferred continuously through GPRS to a central database. The users are able to view the current location of each truck in the collection stage via a web-based application and thereby manage the fleet. The trucks positions and trash bin information are displayed on a digital map, which is made available by a map server. Thus, the solid waste of the bin and the truck are being monitored using the developed system.

LCA comparison of container systems in municipal solid waste management

The planning and design of integrated municipal solid waste management (MSWM) systems requires accurate environmental impact evaluation of the systems and their components. This research assessed, quantified and compared the environmental impact of the first stage of the most used MSW container systems. The comparison was based on factors such as the volume of the containers, from small bins of 60-80l to containers of 2400l, and on the manufactured materials, steel and high-density polyethylene (HDPE). Also, some parameters such as frequency of collections, waste generation, filling percentage and waste container contents, were established to obtain comparable systems. The methodological framework of the analysis was the life cycle assessment (LCA), and the impact assessment method was based on CML 2 baseline 2000. Results indicated that, for the same volume, the collection systems that use HDPE waste containers had more of an impact than those using steel waste containers, in terms of abiotic depletion, global warming, ozone layer depletion, acidification, eutrophication, photochemical oxidation, human toxicity and terrestrial ecotoxicity. Besides, the collection systems using small HDPE bins (60l or 80l) had most impact while systems using big steel containers (2400l) had less impact. Subsequent sensitivity analysis about the parameters established demonstrated that they could change the ultimate environmental impact of each waste container collection system, but that the comparative relationship between systems was similar.