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Feature extraction using Hough transform for solid waste bin level detection and classification

Hannan MA, Zaila WA, Arebey M, Begum RA, Basri H

Environ Monit Assess, 2014 Sep;186(9):5381-91.
PMID: 24829160 DOI: 10.1007/s10661-014-3786-6

This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image's gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.
An automated solid waste bin level detection system using a gray level aura matrix

Hannan MA, Arebey M, Begum RA, Basri H

Waste Manag, 2012 Dec;32(12):2229-38.
PMID: 22749722 DOI: 10.1016/j.wasman.2012.06.002

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

Arebey M, Hannan MA, Begum RA, Basri H

J Environ Manage, 2012 Aug 15;104:9-18.
PMID: 22484654 DOI: 10.1016/j.jenvman.2012.03.035

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

Hannan MA, Arebey M, Begum RA, Basri H

Waste Manag, 2011 Dec;31(12):2406-13.
PMID: 21871788 DOI: 10.1016/j.wasman.2011.07.022

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

Arebey M, Hannan MA, Basri H, Begum RA, Abdullah H

Environ Monit Assess, 2011 Jun;177(1-4):399-408.
PMID: 20703798 DOI: 10.1007/s10661-010-1642-x

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.
Factors and values of willingness to pay for improved construction waste management--a perspective of Malaysian contractors

Begum RA, Siwar C, Pereira JJ, Jaafar AH

Waste Manag, 2007;27(12):1902-9.
PMID: 17110094

Malaysia is facing an increase in the generation of waste and of accompanying problems with the disposal of this waste. In the last two decades, extensive building and infrastructure development projects have led to an increase in the generation of construction waste material. The construction industry has a substantial impact on the environment, and its environmental effects are in direct relation to the quality and quantity of the waste it generates. This paper discusses general characteristics of the construction contractors, the contractors' willingness to pay (WTP) for improved construction waste management, determining factors which affect the amount of their willingness to pay, and suggestions and policy implications in the perspective of construction waste management in Malaysia. The data in this study is based on contractors registered with the construction industry development board (CIDB) of Malaysia. Employing the open ended contingent valuation method, the study assessed the contractors' average maximum WTP for improved construction waste management to be RM69.88 (1US$=3.6 RM) per tonne of waste. The result shows that the average maximum WTP is higher for large contractors than for medium and small contractors. The highest average maximum WTP value is RM88.00 for Group A (large contractors) RM78.25 for Group B (medium-size contractors) and RM55.80 for Group C (small contractors). One of the contributions of this study is to highlight the difference of CIDB registration grade in the WTP for improved construction waste management. It is found that contractors' WTP for improved waste collection and disposal services increases with the increase in contractors' current paid up capital. The identified factors and determinants of the WTP will assist the formulation of appropriate policies in addressing the construction waste problem in Malaysia and indirectly improve the quality of construction in the country.
Content-based image retrieval system for solid waste bin level detection and performance evaluation

Hannan MA, Arebey M, Begum RA, Basri H, Al Mamun MA

Waste Manag, 2016 Apr;50:10-9.
PMID: 26868844 DOI: 10.1016/j.wasman.2016.01.046

This paper presents a CBIR system to investigate the use of image retrieval with an extracted texture from the image of a bin to detect the bin level. Various similarity distances like Euclidean, Bhattacharyya, Chi-squared, Cosine, and EMD are used with the CBIR system for calculating and comparing the distance between a query image and the images in a database to obtain the highest performance. In this study, the performance metrics is based on two quantitative evaluation criteria. The first one is the average retrieval rate based on the precision-recall graph and the second is the use of F1 measure which is the weighted harmonic mean of precision and recall. In case of feature extraction, texture is used as an image feature for bin level detection system. Various experiments are conducted with different features extraction techniques like Gabor wavelet filter, gray level co-occurrence matrix (GLCM), and gray level aura matrix (GLAM) to identify the level of the bin and its surrounding area. Intensive tests are conducted among 250bin images to assess the accuracy of the proposed feature extraction techniques. The average retrieval rate is used to evaluate the performance of the retrieval system. The result shows that, the EMD distance achieved high accuracy and provides better performance than the other distances.
Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization

Akhtar M, Hannan MA, Begum RA, Basri H, Scavino E

Waste Manag, 2017 Mar;61:117-128.
PMID: 28153405 DOI: 10.1016/j.wasman.2017.01.022

Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts.
Fulltext Assessing the cost burden of dengue infection to households in Seremban, Malaysia

Mia MS, Begum RA, Er AC, Pereira JJ

Southeast Asian J. Trop. Med. Public Health, 2016 Nov;47(6):1167-76.
PMID: 29634177

Dengue is endemic in all parts of Malaysia. However, there is limited data regarding the cost burden of this disease at household level. We aimed to
examine the cost of dengue infection at the household level in Seremban District,
Malaysia. This cost assessment can provide an insight to policy-makers about
economic impact of dengue infection in order to guide and prioritize control strategies.
The data were collected via interview. We evaluated120 previous dengue
infection patients registered at the Tuanku Ja’afar Hospital, Seremban District,
Malaysia. The average duration of dengue illness was 9.69 days. The average
household days lost was 18.7; students lost an average of 6.3 days of school and
patients and caregivers lost an average of 12.5 days of work. The mean total cost
per case of dengue infection was estimated to be USD365.16 with the indirect
cost being USD327.90 (89.8% of the total cost) and the direct cost being USD37.26
(10.2% of the total cost). Our findings suggest each episode of dengue infection
imposes a significant financial burden at the household level in Seremban District,
Malaysia; most of the burden being indirect cost. This cost needs to be factored
into the overall cost to society of dengue infection. This data can inform policy
makers when allocating resources to manage public health problems in Malaysia.
Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm

Hannan MA, Akhtar M, Begum RA, Basri H, Hussain A, Scavino E

Waste Manag, 2018 Jan;71:31-41.
PMID: 29079284 DOI: 10.1016/j.wasman.2017.10.019

Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts.
Impacts of climate change on oil palm production in Malaysia

Sarkar MSK, Begum RA, Pereira JJ

Environ Sci Pollut Res Int, 2020 Mar;27(9):9760-9770.
PMID: 31925690 DOI: 10.1007/s11356-020-07601-1

Studies reveal that climate change (CC) has higher negative impacts on agricultural production than positive impacts. Therefore, this article attempts to explore the impacts of CC on oil palm production in Malaysia and provides mitigation and adaptation strategies towards reducing such impacts. The multiple regression analysis is applied to assess the impacts of CC on oil palm production by using time series data in the period of 1980 to 2010. A negative and significant relationship is found between annual average temperature and oil palm production. If temperature rises by 1 °C, 2 °C, 3 °C, and 4 °C, production of oil palm can decrease from a range of 10 to 41%. This article has also found a negative impact of sea level rise (SLR) on oil palm production. Findings reveal that if areas under oil palm production decrease by 2%, 4%, and 8% due to SLR of 0.5, 1, and 2 m, oil palm production can decrease by 1.98%, 3.96%, and 7.92%, respectively, indicating that CC has a significant impact on the reduction of oil palm production in Malaysia, ultimately affecting the sustainability of oil palm sector in Malaysia. Finally, this study suggests to practice appropriate mitigation and adaptation strategies, including promotion and development of climate resilient varieties, soil and water conservation, afforestation, insurance and other risk transfer mechanisms, emission reduction technology, protection of coastal flooding for reducing the impacts of CC on oil palm production.
Fulltext Trends of dengue infections in Malaysia, 2000-2010

Mia MS, Begum RA, Er AC, Abidin RD, Pereira JJ

Asian Pac J Trop Med, 2013 Jun;6(6):462-6.
PMID: 23711707 DOI: 10.1016/S1995-7645(13)60075-9

OBJECTIVE: To analyze trends of dengue incidences and deaths in Malaysia from 2000 to 2010 as well as the predominant dengue virus serotypes during the last decade.
METHODS: We used the national data on annual reported cases, deaths, incidence rate, mortality rate, and case fatality rate of dengue fever (DF) and dengue hemorrhagic fever (DHF) as well as dengue virus serotypes prevalent in Malaysia during the last decade. Trend/ regression lines were fitted to investigate the trend of dengue incidences and deaths due to the disease for a 11-year period (2000-2010). For the distribution of national incidence rate, mortality rate, and case fatality rate of DF and DHF, descriptive statistics using mean and 95% confidence intervals (CI 39) for means, and range were applied.
RESULTS: The number of dengue cases and number of deaths have increased, on average, by 14% and 8% per year respectively. The average annual incidence rate of DF per 100 000 populations was higher as compared to that of DHF. Conversely, the yearly mean mortality rate of DHF per 100 000 populations was greater than that of DF. The simultaneous circulation of all four dengue serotypes has been found in Malaysia. But a particular dengue virus serotype predominates for at least two years before it becomes replaced by another serotype.
CONCLUSIONS: The dengue situation in Malaysia has worsened with an increasing number of reported cases and deaths during the last decade. The increasing trend of dengue highlights the need for a more systematic surveillance and reporting of the disease.
Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model

Aghajani Mir M, Taherei Ghazvinei P, Sulaiman NM, Basri NE, Saheri S, Mahmood NZ, et al.

J Environ Manage, 2016 Jan 15;166:109-15.
PMID: 26496840 DOI: 10.1016/j.jenvman.2015.09.028

Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management.
A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges

Hannan MA, Abdulla Al Mamun M, Hussain A, Basri H, Begum RA

Waste Manag, 2015 Sep;43:509-23.
PMID: 26072186 DOI: 10.1016/j.wasman.2015.05.033

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.

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