Artificial intelligence for waste management in smart cities: a review

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-019-01228-7 · Cited by 6,909

What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050

Kaza, S., Yao, L. C., Bhada-Tata, P., Van Woerden, F., & Levine, D. (2018) · doi:10.1596/978-1-4648-1329-0 · Cited by 6,126

Waste Mismanagement in Developing Countries: A Review of Global Issues

Ferronato, N., & Torretta, V. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16061060 · Cited by 2,293

Evaluating scenarios toward zero plastic pollution

Lau, W. W. Y., Shiran, Y., Bailey, R. M., Cook, E., Stuchtey, M. R., Koskella, J., Velis, C. A., Godfrey, L., Boucher, J., Murphy, M. B., et al. (2020) · Science · doi:10.1126/science.aba9475 · Cited by 1,766

Artificial Intelligence and the Public Sector—Applications and Challenges

Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019) · International Journal of Public Administration · doi:10.1080/01900692.2018.1498103 · Cited by 1,341 · cited 1×

The Global Rise of Zero Liquid Discharge for Wastewater Management: Drivers, Technologies, and Future Directions

Tong, T., & Elimelech, M. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b01000 · Cited by 1,126

Cost, environmental impact, and resilience of renewable energy under a changing climate: a review

Osman, A. I., Chen, L., Yang, M., Msigwa, G., Farghali, M., Fawzy, S., Rooney, D. W., & Yap, P.-S. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-022-01532-8 · Cited by 1,048

Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †

Bouktif, S., Fiaz, A., Ouni, A., & Serhani, M. A. (2018) · Energies · doi:10.3390/en11071636 · Cited by 941

Microplastic sources, formation, toxicity and remediation: a review

Osman, A. I., Hosny, M., Eltaweil, A. S., Omar, S., Elgarahy, A. M., Farghali, M. R. F., Yap, P., Wu, Y. S., Nagandran, S., Batumalaie, K., et al. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-023-01593-3 · Cited by 920

Circular economy strategies for combating climate change and other environmental issues

Yang, M., Chen, L., Wang, J., Msigwa, G., Osman, A. I., Fawzy, S., Rooney, D. W., & Yap, P.-S. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-022-01499-6 · Cited by 835

Strategies to save energy in the context of the energy crisis: a review

Farghali, M. R. F., Osman, A. I., Mohamed, I. M. A., Chen, Z., Chen, L., Ihara, I., Yap, P., & Rooney, D. W. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-023-01591-5 · Cited by 760

A review on automated sorting of source-separated municipal solid waste for recycling

Gundupalli, S. P., Hait, S., & Thakur, A. (2017) · Waste Management · doi:10.1016/j.wasman.2016.09.015 · Cited by 583

Environmental pollution: causes, effects, and the remedies

Ukaogo, P. O., Ewuzie, U., & Onwuka, C. V. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819001-2.00021-8 · Cited by 577

Sorption, transport and biodegradation – An insight into bioavailability of persistent organic pollutants in soil

Ren, X., Zeng, G., Tang, L., Wang, J., Wan, J., Liu, Y., Yu, J., Yi, H., Ye, S., & Deng, R. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.08.089 · Cited by 572

Artificial intelligence applications in solid waste management: A systematic research review

Abdallah, M., Talib, M. W. A., Feroz, S., Nasir, Q., Abdalla, H., & Mahfood, B. (2020) · Waste Management · doi:10.1016/j.wasman.2020.04.057 · Cited by 529

Pyrolysis Study of Polypropylene and Polyethylene Into Premium Oil Products

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Intelligent Waste Classification System Using Deep Learning Convolutional Neural Network

Olugboja, A. M., & Wang, Z. (2019) · Procedia Manufacturing · doi:10.1016/j.promfg.2019.05.086 · Cited by 443

Barriers to smart waste management for a circular economy in China

Zhang, A., Venkatesh, V. G., Liu, Y., Wan, M., Qu, T., & Huisingh, D. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.118198 · Cited by 431

Applied Machine Learning for Prediction of CO 2 Adsorption on Biomass Waste-Derived Porous Carbons

Yuan, X., Suvarna, M., Low, S., Dissanayake, P. D., Lee, K. B., Li, J., Wang, X., & Ok, Y. S. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c01849 · Cited by 412

Qualitative data analysis: conceptual and practical considerations

Liamputtong, P. (2009) · Health Promotion Journal of Australia · doi:10.1071/he09133 · Cited by 411

Adoption of artificial intelligence in smart cities: A comprehensive review

Herath, H. M. K. K. M. B., & Mittal, M. (2022) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2022.100076 · Cited by 409

Green construction for low-carbon cities: a review

Chen, L., Huang, L., Hua, J., Chen, Z., Wei, L., Osman, A. I., Fawzy, S., Rooney, D. W., Dong, L., & Yap, P. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-022-01544-4 · Cited by 408

Application of machine learning methods for the prediction of organic solid waste treatment and recycling processes: A review

Guo, H., Wu, S., Tian, Y., Zhang, J., & Liu, H. (2020) · Bioresource Technology · doi:10.1016/j.biortech.2020.124114 · Cited by 395

Forecasting municipal solid waste generation using artificial intelligence modelling approaches

Abbasi, M., & Hanandeh, A. E. (2016) · Waste Management · doi:10.1016/j.wasman.2016.05.018 · Cited by 381

Recycling of Organic Wastes in Agriculture: An Environmental Perspective

Sharma, B., Vaish, B., Monika, Singh, U. K., Singh, P., & Singh, R. P. (2019) · International Journal of Environmental Research · doi:10.1007/s41742-019-00175-y · Cited by 340

The sustainability of artificial intelligence: an urbanistic viewpoint from the lens of smart and sustainable cities

Yigitcanlar, T., & Cugurullo, F. (2020) · Sustainability · doi:10.3390/su12208548 · Cited by 337

Recycling municipal, agricultural and industrial waste into energy, fertilizers, food and construction materials, and economic feasibility: a review

Peng, X., Jiang, Y., Chen, Z., Osman, A. I., Farghali, M., Rooney, D. W., & Yap, P.-S. (2023) · Environmental Chemistry Letters · doi:10.1007/s10311-022-01551-5 · Cited by 333

Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures

Yigitcanlar, T., Mehmood, R., & Corchado, J. M. (2021) · Sustainability · doi:10.3390/su13168952 · Cited by 319

Deep Eutectic Solvents for Pretreatment, Extraction, and Catalysis of Biomass and Food Waste

Kalhor, P., & Ghandi, K. (2019) · Molecules · doi:10.3390/molecules24224012 · Cited by 305

Technologies and decision support systems to aid solid-waste management: a systematic review

Melaré, A. V. D. S., González, S. M., Faceli, K., & Casadei, V. (2016) · Waste Management · doi:10.1016/j.wasman.2016.10.045 · Cited by 296

Machine learning methods for modelling the gasification and pyrolysis of biomass and waste

Ascher, S., Watson, I., & You, S. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.111902 · Cited by 288

Assessing the impact of industrial waste on environment and mitigation strategies: A comprehensive review

Gaur, V. K., Sharma, P., Sirohi, R., Awasthi, M. K., Dussap, C., & Pandey, A. (2020) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2020.123019 · Cited by 280

Slow pyrolysis as a platform for negative emissions technology: An integration of machine learning models, life cycle assessment, and economic analysis

Cheng, F., Luo, H., & Colosi, L. M. (2020) · Energy Conversion and Management · doi:10.1016/j.enconman.2020.113258 · Cited by 271

Application of machine learning algorithms in municipal solid waste management: A mini review

Xia, W., Jiang, Y., Chen, X., & Zhao, R. (2021) · Waste Management & Research The Journal for a Sustainable Circular Economy · doi:10.1177/0734242x211033716 · Cited by 265

A roadmap for development of sustainable E-waste management system in India

Wath, S. B., Vaidya, A. N., Dutt, P., & Chakrabarti, T. (2010) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2010.09.030 · Cited by 247

Artificial Intelligence in the Sorting of Municipal Waste as an Enabler of the Circular Economy

Wilts, H., Garcia, B. R., Garlito, R. G., Gómez, L. S., & Prieto, E. G. (2021) · Resources · doi:10.3390/resources10040028 · Cited by 242

Waste image classification based on transfer learning and convolutional neural network

Zhang, Q., Yang, Q., Zhang, X., Bao, Q., Su, J., & Liu, X. (2021) · Waste Management · doi:10.1016/j.wasman.2021.08.038 · Cited by 231

A strength prediction model using artificial intelligence for recycling waste tailings as cemented paste backfill

Qi, C., Fourie, A. B., Chen, Q., & Zhang, Q. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.02.154 · Cited by 226

Environmental Pollution from Illegal Waste Disposal and Health Effects: A Review on the “Triangle of Death”

Triassi, M., Alfano, R., Illario, M., Nardone, A., Caporale, O., & Montuori, P. (2015) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph120201216 · Cited by 221

Carbon emissions under different domestic waste treatment modes induced by garbage classification: Case study in pilot communities in Shanghai, China

Chen, S., Huang, J., Xiao, T., Gao, J. Q., Bai, J., Luo, W. P., & Dong, B. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.137193 · Cited by 221

A Review on Prediction of Municipal Solid Waste Generation Models

Kolekar, K. A., Hazra, T., & Chakrabarty, S. N. (2016) · Procedia Environmental Sciences · doi:10.1016/j.proenv.2016.07.087 · Cited by 220

Artificial intelligence applications for sustainable solid waste management practices in Australia: A systematic review

Andeobu, L., Wibowo, S., & Grandhi, S. (2022) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2022.155389 · Cited by 220

Gas turbine performance prediction via machine learning

Liu, Z., & Karimi, I. A. (2019) · Energy · doi:10.1016/j.energy.2019.116627 · Cited by 211

Integration of biogas systems into a carbon zero and hydrogen economy: a review

Farghali, M., Osman, A. I., Umetsu, K., & Rooney, D. W. (2022) · Environmental Chemistry Letters · doi:10.1007/s10311-022-01468-z · Cited by 209

Recyclable waste image recognition based on deep learning

Zhang, Q., Zhang, X., Mu, X., Wang, Z., Tian, R., Wang, X., & Liu, X. (2021) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2021.105636 · Cited by 207

Environmental planning based on reduce, reuse, recycle and recover using artificial intelligence

Yu, K. H., Zhang, Y., Li, D., Montenegro, C., & Kumar, P. M. (2020) · Environmental Impact Assessment Review · doi:10.1016/j.eiar.2020.106492 · Cited by 195

Prediction of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach

Cao, H., Xin, Y., & Yuan, Q. (2015) · Bioresource Technology · doi:10.1016/j.biortech.2015.12.024 · Cited by 194

Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization

Akhtar, M., Hannan, M. A., Begum, R. A., Basri, H., & Scavino, E. (2017) · Waste Management · doi:10.1016/j.wasman.2017.01.022 · Cited by 189

Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening

Li, J., Pan, L., Suvarna, M., & Wang, X. (2021) · Chemical Engineering Journal · doi:10.1016/j.cej.2021.131285 · Cited by 185

Big data analytics to identify illegal construction waste dumping: A Hong Kong study

Lu, W. (2018) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2018.10.039 · Cited by 184

Estimation of the generation rate of different types of plastic wastes and possible revenue recovery from informal recycling

Kumar, A., Samadder, S. R., Kumar, N., & Singh, C. (2018) · Waste Management · doi:10.1016/j.wasman.2018.08.045 · Cited by 180

Robotic Waste Sorting Technology: Toward a Vision-Based Categorization System for the Industrial Robotic Separation of Recyclable Waste

Koskinopoulou, M., Raptopoulos, F., Papadopoulos, G., Mavrakis, N., & Maniadakis, M. (2021) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2021.3066040 · Cited by 178

Common Garbage Classification Using MobileNet

Rabano, S. L., Cabatuan, M. K., Sybingco, E., Dadios, E. P., & Calilung, E. J. (2018) · IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) · doi:10.1109/hnicem.2018.8666300 · Cited by 173

Environmental impacts of waste management and valorisation pathways for surplus bread in Sweden

Brancoli, P., Bolton, K., & Eriksson, M. (2020) · Waste Management · doi:10.1016/j.wasman.2020.07.043 · Cited by 169

Investigation of co-combustion characteristics of sewage sludge and coffee grounds mixtures using thermogravimetric analysis coupled to artificial neural networks modeling

Chen, J., Liu, J., He, Y., Huang, L., Sun, S., Sun, J., Chang, K., Kuo, J., Huang, S., & Ning, X. (2016) · Bioresource Technology · doi:10.1016/j.biortech.2016.11.069 · Cited by 160

An artificial intelligence based approach to predicting syngas composition for downdraft biomass gasification

Mutlu, A. Y., & Yücel, Ö. (2018) · Energy · doi:10.1016/j.energy.2018.09.131 · Cited by 160

Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities

Kontokosta, C. E., Hong, B., Johnson, N. E., & Starobin, D. (2018) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2018.03.004 · Cited by 159

Vision-based robotic system for on-site construction and demolition waste sorting and recycling

Wang, Z., Li, H., & Yang, X. (2020) · Journal of Building Engineering · doi:10.1016/j.jobe.2020.101769 · Cited by 159

Comparison of Random Forest and Gradient Boosting Machine Models for Predicting Demolition Waste Based on Small Datasets and Categorical Variables

Cha, G.-W., Moon, H. J., & Kim, Y. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18168530 · Cited by 158

Toward smarter management and recovery of municipal solid waste: A critical review on deep learning approaches

Lin, K., Zhao, Y., Kuo, J., Deng, H., Cui, F., Zhang, Z., Zhang, M., Zhao, C., Gao, X., Zhou, T., et al. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.130943 · Cited by 157

Deep Learning for Plastic Waste Classification System

Bobulski, J., & Kubanek, M. (2021) · Applied Computational Intelligence and Soft Computing · doi:10.1155/2021/6626948 · Cited by 150

Academic Policy Regarding Sustainability and Artificial Intelligence (AI)

Tanveer, M., Hassan, S., & Bhaumik, A. (2020) · Sustainability · doi:10.3390/su12229435 · Cited by 149

Implications of COVID-19 on global environmental pollution and carbon emissions with strategies for sustainability in the COVID-19 era

Yang, M., Chen, L., Msigwa, G., Tang, K. H. D., & Yap, P. (2021) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2021.151657 · Cited by 143

Robot for automatic waste sorting on construction sites

Chen, X., Huang, H., Liu, Y., Li, J., & Liu, M. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104387 · Cited by 141

Patterns of waste generation: A gradient boosting model for short-term waste prediction in New York City

Johnson, N. E., Ianiuk, O., Cazap, D., Liu, L., Starobin, D., Dobler, G., & Ghandehari, M. (2017) · Waste Management · doi:10.1016/j.wasman.2017.01.037 · Cited by 138

Applying machine learning approach in recycling

Özdemir, M. E., Ali, Z., Subeshan, B., & Asmatulu, E. (2021) · Journal of Material Cycles and Waste Management · doi:10.1007/s10163-021-01182-y · Cited by 138

Artificial Intelligence in the Urban Environment: Smart Cities as Models for Developing Innovation and Sustainability

Ortega-Fernández, A., Martín‐Rojas, R., & Morales, V. J. G. (2020) · Sustainability · doi:10.3390/su12197860 · Cited by 137

A review on modern and smart technologies for efficient waste disposal and management

Mukherjee, A. G., Wanjari, U. R., Chakraborty, R., Renu, K., Vellingiri, B., George, A., Rajan, R. S., & Gopalakrishnan, A. V. (2021) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.113347 · Cited by 136

Machine learning approach for a circular economy with waste recycling in smart cities

Chen, X. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.01.193 · Cited by 134

Artificial intelligence-based microfluidic platforms for the sensitive detection of environmental pollutants: Recent advances and prospects

Pouyanfar, N., Harofte, S. Z., Soltani, M., Siavashy, S., Asadian, E., Ghorbani‐Bidkorbeh, F., Keçili, R., & Hussain, C. M. (2022) · Trends in Environmental Analytical Chemistry · doi:10.1016/j.teac.2022.e00160 · Cited by 134

Developing an applied algorithm for multi-trip vehicle routing problem with time windows in urban waste collection: A case study

Tırkolaee, E. B., Abbasian, P., Soltani, M., & Ghaffarian, S. A. (2019) · Waste Management & Research The Journal for a Sustainable Circular Economy · doi:10.1177/0734242x18807001 · Cited by 131

Waste classification using AutoEncoder network with integrated feature selection method in convolutional neural network models

Toğaçar, M., Ergen, B., & Cömert, Z. (2019) · Measurement · doi:10.1016/j.measurement.2019.107459 · Cited by 128

Forecasting municipal solid waste generation using artificial intelligence models—a case study in India

Soni, U., Roy, A., Verma, A., & Jain, V. (2019) · SN Applied Sciences · doi:10.1007/s42452-018-0157-x · Cited by 126

Prognostication of energy use and environmental impacts for recycle system of municipal solid waste management

Nabavi‐Pelesaraei, A., Bayat, R., Hosseinzadeh-Bandbafha, H., Afrasyabi, H., & Berrada, A. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2017.04.033 · Cited by 125

Comparative study of predicting hospital solid waste generation using multiple linear regression and artificial intelligence

Golbaz, S., Nabizadeh, R., & Sajadi, H. S. (2019) · Journal of Environmental Health Science and Engineering · doi:10.1007/s40201-018-00324-z · Cited by 122

Landfill area estimation based on solid waste collection prediction using ANN model and final waste disposal options

Hoque, M. M., & Rahman, M. T. U. (2020) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.120387 · Cited by 121

Efficient Recognition and Automatic Sorting Technology of Waste Textiles Based on Online Near infrared Spectroscopy and Convolutional Neural Network

Du, W., Zheng, J., Li, W., Liu, Z., Wang, H., & Xi, H. (2022) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2022.106157 · Cited by 120

Design a smart waste bin for smart waste management

Wijaya, A. S., Zainuddin, Z., & Niswar, M. (2017) · International Conference on Instrumentation, Control, and Automation (ICA) · doi:10.1109/ica.2017.8068414 · Cited by 119

A Waste Classification Method Based on a Multilayer Hybrid Convolution Neural Network

Shi, C., Tan, C., Wang, T., & Wang, L. (2021) · Applied Sciences · doi:10.3390/app11188572 · Cited by 119

Artificial neural network model to predict behavior of biogas production curve from mixed lignocellulosic co-substrates

Ghatak, M. D., & Ghatak, A. (2018) · Fuel · doi:10.1016/j.fuel.2018.05.051 · Cited by 118

Deep learning networks for real-time regional domestic waste detection

Mao, W., Chen, W., Fathurrahman, H. I. K., & Lin, Y. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.131096 · Cited by 117

Recent advances in applications of artificial intelligence in solid waste management: A review

Ihsanullah, I., Alam, G., Jamal, A., & Shaik, F. (2022) · Chemosphere · doi:10.1016/j.chemosphere.2022.136631 · Cited by 117

Sustainability Indicators Concerning Waste Management for Implementation of the Circular Economy Model on the University of Lome (Togo) Campus

Salguero-Puerta, L., Leyva‐Díaz, J. C., Cortés‐García, F. J., & Moreno, V. M. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16122234 · Cited by 111

Application of artificial intelligence to enhance collection of E-waste: A potential solution for household WEEE collection and segregation in India

Madhav, A. V. S., Rajaraman, R., Sriraman, H., & Kiliroor, C. C. (2021) · Waste Management & Research The Journal for a Sustainable Circular Economy · doi:10.1177/0734242x211052846 · Cited by 107

Combining an artificial intelligence algorithm and a novel vehicle for sustainable e-waste collection

Nowakowski, P., Szwarc, K., & Boryczka, U. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.138726 · Cited by 105

Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill

Abunama, T., Othman, F. B., Ansari, M., & El‐Shafie, A. (2018) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-3749-5 · Cited by 103

Internet of things-based urban waste management system for smart cities using a Cuckoo Search Algorithm

Alqahtani, F. H., Al-Makhadmeh, Z., Tolba, A. K. R., & Said, W. (2020) · Cluster Computing · doi:10.1007/s10586-020-03126-x · Cited by 103

Alleviating corporate environmental pollution threats toward public health and safety: The role of smart city and artificial intelligence

Liu, W., Xu, Y., Fan, D., Li, Y., Shao, X., & Zheng, J. (2021) · Safety Science · doi:10.1016/j.ssci.2021.105433 · Cited by 103

Artificial intelligence for planning of energy and waste management

Huang, J., & Koroteev, D. D. (2021) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2021.101426 · Cited by 102

Application of artificial intelligence neural network modeling to predict the generation of domestic, commercial and construction wastes

Coşkuner, G., Jassim, M. S., Zontul, M., & Karateke, S. (2020) · Waste Management & Research The Journal for a Sustainable Circular Economy · doi:10.1177/0734242x20935181 · Cited by 100

Artificial intelligence and machine learning approaches in composting process: A review

Temel, F. A., Yolcu, Ö. C., & Turan, N. G. (2023) · Bioresource Technology · doi:10.1016/j.biortech.2022.128539 · Cited by 99

Deep Learning and Remote Sensing: Detection of Dumping Waste Using UAV

Youme, O., Bayet, T., Dembélé, J. M., & Cambier, C. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.05.037 · Cited by 95

Deep Convolutional Neural Networks Object Detector for Real-Time Waste Identification

Melinte, O., Travediu, A.-M., & Dumitriu, D. N. (2020) · Applied Sciences · doi:10.3390/app10207301 · Cited by 95

Applications of computational chemistry, artificial intelligence, and machine learning in aquatic chemistry research

He, L., Bai, L., Dionysiou, D. D., Wei, Z., Spinney, R., Chu, C., Lin, Z., & Xiao, R. (2021) · Chemical Engineering Journal · doi:10.1016/j.cej.2021.131810 · Cited by 94

Automation of Waste Sorting with Deep Learning

de Sousa, J. B., Rebelo, A., & Cardoso, J. S. (2019) · Workshop of Computer Vision (WVC) · doi:10.1109/wvc.2019.8876924 · Cited by 92

Applied machine learning for prediction of waste plastic pyrolysis towards valuable fuel and chemicals production

Cheng, Y., Ekici, E., Yıldız, G., Yang, Y., Coward, B., & Wang, J. (2023) · Journal of Analytical and Applied Pyrolysis · doi:10.1016/j.jaap.2023.105857 · Cited by 92

Dumping, waste management and ecological security: Evidence from England

Liu, Y., Kong, F., & González, E. D. R. S. (2016) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.12.097 · Cited by 91

Development of a Prediction Model for Demolition Waste Generation Using a Random Forest Algorithm Based on Small DataSets

Cha, G.-W., Moon, H. J., Kim, Y., Hong, W.-H., Hwang, J.-H., Park, W.-J., & Kim, Y.-C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17196997 · Cited by 91

A hybrid data-driven and mechanistic modelling approach for hydrothermal gasification

Li, J., Suvarna, M., Pan, L., Zhao, Y., & Wang, X. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.117674 · Cited by 91

Evolution of physicochemical properties and bacterial community in aerobic composting of swine manure based on a patent compost tray

Wei, Y., Liang, Z., & Zhang, Y. (2021) · Bioresource Technology · doi:10.1016/j.biortech.2021.126136 · Cited by 90

Optimal Routing of Solid Waste Collection Trucks: A Review of Methods

Sulemana, A., Donkor, E. A., Forkuo, E. K., & Oduro–Kwarteng, S. (2018) · Journal of Engineering · doi:10.1155/2018/4586376 · Cited by 89

New insights into regional differences of the predictions of municipal solid waste generation rates using artificial neural networks

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Artificial neural network modelling of the amount of separately-collected household packaging waste

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Forecasting of municipal solid waste generation using non-linear autoregressive (NAR) neural models

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A comparison of machine learning algorithms for estimation of higher heating values of biomass and fossil fuels from ultimate analysis

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Smart City Platform Development for an Automated Waste Collection System

Popa, C. L., Căruțașu, G., Coteț, C. E., Căruțașu, N. L., & Dobrescu, T. G. (2017) · Sustainability · doi:10.3390/su9112064 · Cited by 80

Learning to Identify Illegal Landfills through Scene Classification in Aerial Images

Torres, R. N., & Fraternali, P. (2021) · Remote Sensing · doi:10.3390/rs13224520 · Cited by 80

How does the “Zero-waste City” strategy contribute to carbon footprint reduction in China?

Yang, G., Zhang, Q., Zhao, Z., & Zhou, C. (2022) · Waste Management · doi:10.1016/j.wasman.2022.11.032 · Cited by 80

Smart Bin: Internet-of-Things Garbage Monitoring System

Mustafa, M., & Azir, K. N. F. K. (2017) · MATEC Web of Conferences · doi:10.1051/matecconf/201714001030 · Cited by 79

Development of an Artificial Intelligence Model to Recognise Construction Waste by Applying Image Data Augmentation and Transfer Learning

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An IoT-based bin level monitoring system for solid waste management

Ramson, S. R. J., Moni, D. J., Vishnu, S., Anagnostopoulos, T., Kirubaraj, A. A., & Fan, X. (2020) · Journal of Material Cycles and Waste Management · doi:10.1007/s10163-020-01137-9 · Cited by 77

A Systematic Review of Construction and Demolition Waste Management in Australia: Current Practices and Challenges

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SGA: spatial GIS-based genetic algorithm for route optimization of municipal solid waste collection

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RHINOS: A lightweight portable electronic nose for real-time odor quantification in wastewater treatment plants

Burgués, J., Vicente, M. D. E., Doñate, S., & Marco, S. (2021) · iScience · doi:10.1016/j.isci.2021.103371 · Cited by 74

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Generalized models to predict the lower heating value (LHV) of municipal solid waste (MSW)

Wang, D., Tang, Y.-T., He, J. Y., Yang, F. H., & Robinson, D. (2020) · Energy · doi:10.1016/j.energy.2020.119279 · Cited by 73

Development of an automatic sorting robot for construction and demolition waste

Xiao, W., Yang, J., Fang, H., Zhuang, J., Ku, Y., & Zhang, X. (2020) · Clean Technologies and Environmental Policy · doi:10.1007/s10098-020-01922-y · Cited by 72

Opportunities and knowledge gaps in biochemical interventions for mining of resources from solid waste: A special focus on anaerobic digestion

Vyas, S., Prajapati, P., Shah, A. V., Srivastava, V. K., & Varjani, S. (2021) · Fuel · doi:10.1016/j.fuel.2021.122625 · Cited by 72

Remanufacturing with RFID item-level information: Optimization, waste reduction and quality improvement

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A GIS-based novel approach for suitable sanitary landfill site selection using integrated fuzzy analytic hierarchy process and machine learning algorithms

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Transformation from IoT to IoV for waste management in smart cities

Ijemaru, G. K., Ang, L.-M., & Seng, K. P. (2022) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2022.103393 · Cited by 69

A Secure Energy Aware Meta-Heuristic Routing Protocol (SEAMHR) for sustainable IoT-Wireless Sensor Network (WSN)

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A hybrid machine-learning model for predicting the waste generation rate of building demolition projects

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Experimental investigation and AI prediction modelling of ceramic waste powder concrete – An approach towards sustainable construction

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Research on Automatic Garbage Detection System Based on Deep Learning and Narrowband Internet of Things

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Methods to alleviate the inhibition of sludge anaerobic digestion by emerging contaminants: a review

Tawfik, A., Mohsen, M., Ismail, S., Alhajeri, N. S., Osman, A. I., & Rooney, D. W. (2022) · Environmental Chemistry Letters · doi:10.1007/s10311-022-01465-2 · Cited by 65

Optimization of hydrothermal gasification process through machine learning approach: Experimental conditions, product yield and pollution

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Computer Vision Based Two-stage Waste Recognition-Retrieval Algorithm for Waste Classification

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Comprehensive Interrogation on Acetylcholinesterase Inhibition by Ionic Liquids Using Machine Learning and Molecular Modeling

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Optimization of municipal solid waste collection and transportation routes, through linear programming and geographic information system: a case study from Şanlıurfa, Turkey

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Risk assessment and quality improvement of liquid waste management in Taiwan University chemical laboratories

Ho, C., & Chen, M.-S. (2017) · Waste Management · doi:10.1016/j.wasman.2017.09.029 · Cited by 58

IOT Based Smart Garbage Monitoring System Using ZigBee

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Status quo of illegal dumping research: Way forward

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Simulation, prediction and optimization of typical heavy metals immobilization in swine manure composting by using machine learning models and genetic algorithm

Guo, H., Liu, H., & Wu, S. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2022.116266 · Cited by 56

The Design and Implementation of Smart Trash Bin

Fadel, F. (2017) · Academic Journal of Nawroz University · doi:10.25007/ajnu.v6n3a103 · Cited by 55

Fuel from Waste: A Review on Scientific Solution for Waste Management and Environment Conservation

Bhatt, A. K., Bhatia, R. K., Thakur, S., Rana, N., Sharma, V., & Rathour, R. K. (2017) · Energy, environment, and sustainability · doi:10.1007/978-981-10-7518-6_10 · Cited by 55

Optimization of an explosive waste incinerator via an artificial neural network surrogate model

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An analysis of waste gasification and its contribution to China's transition towards carbon neutrality and zero waste cities

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New approach for forecasting demolition waste generation using chi-squared automatic interaction detection (CHAID) method

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A Distributed Architecture for Smart Recycling Using Machine Learning

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Response surface methodology and artificial neural network modelling for enhancing maturity parameters during vermicomposting of floral waste

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IoT based Smart Bin: A Swachh-Bharat Initiative

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Prediction of methane emission from landfills using machine learning models

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Sustainability assessment of biomethanol production via hydrothermal gasification supported by artificial neural network

Fózer, D., Tóth, A. J., Varbanov, P. S., Klemeš, J. J., & Mizsey, P. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.128606 · Cited by 52

Real Time Multipurpose Smart Waste Classification Model for Efficient Recycling in Smart Cities Using Multilayer Convolutional Neural Network and Perceptron

Gondal, A. U., Sadiq, M. I., Ali, T., Irfan, M., Shaf, A., Aamir, M., Shoaib, M., Głowacz, A., Tadeusiewicz, R., & Kańtoch, E. (2021) · Italian National Conference on Sensors · doi:10.3390/s21144916 · Cited by 51

Prediction of carbon dioxide production from green waste composting and identification of critical factors using machine learning algorithms

Li, Y., Li, S., Sun, X., & Hao, D. (2022) · Bioresource Technology · doi:10.1016/j.biortech.2022.127587 · Cited by 51

What drives the ecological quality of surface waters? A review of 11 predictive modeling tools

Visser, H., Evers, N., Bontsema, A., Rost, J., de Niet, A. C., Vethman, P., Mylius, S. D., van der Linden, A., van den Roovaart, J., van Gaalen, F., et al. (2021) · Water Research · doi:10.1016/j.watres.2021.117851 · Cited by 50

Intelligent and Real-Time Detection and Classification Algorithm for Recycled Materials Using Convolutional Neural Networks

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A Study on AI‐based Waste Management Strategies for the COVID‐19 Pandemic

Rubab, S., Khan, M. M. Z. M., Uddin, F., Bangash, Y. A., & Taqvi, S. A. A. (2022) · ChemBioEng Reviews · doi:10.1002/cben.202100044 · Cited by 47

Multi-hydrolytic biocatalyst from organic solid waste and its application in municipal waste activated sludge pre-treatment towards energy recovery

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Waste management in the case of Bahir Dar City near Lake Tana shore in Northwestern Ethiopia: A review

Biruk, A. F. (2017) · African Journal of Environmental Science and Technology · doi:10.5897/ajest2017.2340 · Cited by 44

Key wastes selection and prediction improvement for biogas production through hybrid machine learning methods

Chiu, M., Wen, C.-Y., Hsu, H.-W., & Wang, W. (2022) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2022.102223 · Cited by 44

Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials

Kshirsagar, P. R., Kumar, N., Almulihi, A. H., Alassery, F., Khan, A. I., Islam, S., Rothe, J. P., Jagannadham, D. B. V., & Dekeba, K. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/2073482 · Cited by 44

A 4-DoF Parallel Robot With a Built-in Gripper for Waste Sorting

Leveziel, M., Laurent, G. J., Haouas, W., Michaël Gauthier, A., & Dahmouche, R. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3192582 · Cited by 44

Smart waste bin system: a review

Noiki, A. A., Afolalu, S. A., Abioye, A. A., Bolu, C. A., & Emetere, M. E. (2021) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/655/1/012036 · Cited by 41

Garbage Collection and Sorting with a Mobile Manipulator using Deep Learning and Whole-Body Control

Liu, J., Balatti, P., Ellis, K., Hadjivelichkov, D., Stoyanov, D. V., Ajoudani, A., & Kanoulas, D. (2021) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids47582.2021.9555800 · Cited by 41

Describing health care waste generation rates using regression modeling and principal component analysis

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Developing a Prediction Model of Demolition-Waste Generation-Rate via Principal Component Analysis

Cha, G.-W., Choi, S.-H., Hong, W., & Park, C.-W. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20043159 · Cited by 38

Artificial neural network (ANN) modeling for the prediction of odor emission rates from landfill working surface

Xu, A., Li, R., Chang, H., Xu, Y., Li, X., Lin, G., & Zhao, Y. (2021) · Waste Management · doi:10.1016/j.wasman.2021.11.045 · Cited by 37

Smart waste management practices in smart cities: Current trends and future perspectives

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Transfer learning-based method for automated e-waste recycling in smart cities

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A global literature review of the drivers of indiscriminate dumping of waste: Guiding future research in South Africa

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GIS based MCDM for waste disposal site selection in Dejen town, Ethiopia

Zewdie, M. M., & Yeshanew, S. M. (2023) · Environmental and Sustainability Indicators · doi:10.1016/j.indic.2023.100228 · Cited by 34

The dynamics of indiscriminate/ illegal dumping of waste in Fisantekraal, Cape Town, South Africa

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Real time monitoring of solid waste with customized hardware and Internet of Things

Joshi, L. M., Bharti, R. K., Singh, R., & Malik, P. K. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108262 · Cited by 33

Arduino-based smart garbage monitoring system: Analysis requirement and implementation

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Improving the Sustainability of Regional Development in the Context of Waste Management

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IoT enabled waste management system using ZigBee network

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Pyrolysis of Mixed Plastic Waste: II. Artificial Neural Networks Prediction and Sensitivity Analysis

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Automatic waste detection with few annotated samples: Improving waste management efficiency

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An alternative method to determine the share of fossil carbon in solid refuse-derived fuels – Validation and comparison with three standardized methods

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Litter on the streets - solid waste detection using VHR images

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Smart bin — An “Internet of Things” approach to clean and safe public space

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A Solution for the Full-Load Collection Vehicle Routing Problem With Multiple Trips and Demands: An Application in Beijing

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Modeling of energy and emissions from animal manure using machine learning methods: the case of the Western Mediterranean Region, Turkey

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AIDM-Strat: Augmented Illegal Dumping Monitoring Strategy through Deep Neural Network-Based Spatial Separation Attention of Garbage

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Predicting solid waste generation based on the ensemble artificial intelligence models under uncertainty analysis

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Smart Waste Management System for Bangladesh

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Quantification and mapping of domestic plastic waste using GIS/GPS approach at the city of Guayaquil

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Tracking of bio medical waste using global positioning system

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A Comparison between Two Main Academic Literature Collections: Web of Science and Scopus Databases

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Toward integrated and sustainable waste management system in University of Malaya: UM zero waste campaign

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Design of mobile garbage collection robot based on visual recognition

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An Intelligent Garbage Bin Based on NB-IOT Research Mode

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Measurement and practices for hazardous waste management

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Robotic Dustbin on Wheels

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Accurate Detection of Illegal Dumping Sites Using High Resolution Aerial Photography and Deep Learning

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Cascade reservoirs adaptive refined simulation model based on the mechanism-AI coupling modeling paradigm

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Intelligent Modeling of the Incineration Process in Waste Incineration Power Plant Based on Deep Learning

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In situ process monitoring of nuclear waste glass melts using non-contact microwave sensor

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Vehicle Route Optimization for Solid Waste Management: A Case Study of Maltepe, Istanbul

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Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

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