A Low-Cost Energy Monitoring System with Universal Compatibility and Real-Time Visualization for Enhanced Accessibility and Power Savings

Guardado en:
Detalles Bibliográficos
Publicado en:Sustainability vol. 16, no. 10 (2024), p. 4137
Autor principal: Hashim Raza Khan
Otros Autores: Kazmi, Majida, Lubaba, Muhammad Hashir Bin Khalid, Alam, Urooj, Arshad, Kamran, Assaleh, Khaled, Saad Ahmed Qazi
Publicado:
MDPI AG
Materias:
Acceso en línea:Citation/Abstract
Full Text + Graphics
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

MARC

LEADER 00000nab a2200000uu 4500
001 3059694486
003 UK-CbPIL
022 |a 2071-1050 
024 7 |a 10.3390/su16104137  |2 doi 
035 |a 3059694486 
045 2 |b d20240101  |b d20241231 
084 |a 231634  |2 nlm 
100 1 |a Hashim Raza Khan  |u Neurocomputation Lab, National Center of Artificial Intelligence, Karachi 75270, Pakistan; <email>hashim@neduet.edu.pk</email> (H.R.K.); <email>majidakazmi@neduet.edu.pk</email> (M.K.); <email>lubabarehman16@gmail.com</email> (L.); <email>Mohammadhashirbinkhalid@gmail.com</email> (M.H.B.K.); <email>uroojalam109@gmail.com</email> (U.A.); <email>saadqazi@neduet.edu.pk</email> (S.A.Q.); Faculty of Electrical and Computer Engineering, NED University of Engineering and Technology, Karachi 75270, Pakistan 
245 1 |a A Low-Cost Energy Monitoring System with Universal Compatibility and Real-Time Visualization for Enhanced Accessibility and Power Savings 
260 |b MDPI AG  |c 2024 
513 |a Journal Article 
520 3 |a Energy management is important for both consumers and utility providers. Utility providers are concerned with identifying and reducing energy wastage and thefts. Consumers are interested in reducing their energy consumption and bills. In Pakistan, residential and industrial estates account for nearly 31,000 MW of the maximum total demand, while the transmission and distribution capacity has stalled at about 22,000 MW. This 9000 MW gap in demand and supply, as reported in 2022, has led to frequent load shedding. Although the country now has an excess generation capacity of about 45,000 MW, the aging transmission and distribution network cannot deliver the requisite power at all times. Hence, electricity-related problems are likely to continue for the next few years in the country and the same is true for other low- and middle-income countries (LMICs). Several energy monitoring systems (EnMS) have been proposed, but they face limitations in terms of cost, ease of application, lack of universal installation capability, customization, and data security. The research below focused on the development of an economical, secure, and customizable real-time EnMS. The proposed EnMS comprises low-cost hardware for gathering energy data with universal compatibility, a secured communication module for real-time data transmission, and a dashboard application for visualization of real-time energy consumption in a user-preferred manner, making the information easily accessible and actionable. The experimental results and analysis revealed that approximately 40% cost savings in EnMS development could be achieved compared to other commercially available EnMSs. The performance of the EnMS hardware was evaluated and validated through rigorous on-site experiments. The front-end of the EnMS was assessed through surveys and was found to be interactive and user-friendly for the target clients. The developed EnMS architecture was found to be an economical end-product and an appropriate approach for small and medium clients such as residential, institutional, commercial, and industrial consumers, all on one platform. 
653 |a Load 
653 |a Behavior 
653 |a Consumers 
653 |a Infrastructure 
653 |a Electricity 
653 |a Communication 
653 |a Open source software 
653 |a Renewable resources 
653 |a Software services 
653 |a Design 
653 |a Energy resources 
653 |a Cost control 
653 |a Cloud computing 
653 |a Monitoring systems 
653 |a Compatible hardware 
653 |a Energy consumption 
653 |a Internet of Things 
653 |a Wireless access points 
700 1 |a Kazmi, Majida  |u Neurocomputation Lab, National Center of Artificial Intelligence, Karachi 75270, Pakistan; <email>hashim@neduet.edu.pk</email> (H.R.K.); <email>majidakazmi@neduet.edu.pk</email> (M.K.); <email>lubabarehman16@gmail.com</email> (L.); <email>Mohammadhashirbinkhalid@gmail.com</email> (M.H.B.K.); <email>uroojalam109@gmail.com</email> (U.A.); <email>saadqazi@neduet.edu.pk</email> (S.A.Q.); Faculty of Electrical and Computer Engineering, NED University of Engineering and Technology, Karachi 75270, Pakistan 
700 1 |a Lubaba  |u Neurocomputation Lab, National Center of Artificial Intelligence, Karachi 75270, Pakistan; <email>hashim@neduet.edu.pk</email> (H.R.K.); <email>majidakazmi@neduet.edu.pk</email> (M.K.); <email>lubabarehman16@gmail.com</email> (L.); <email>Mohammadhashirbinkhalid@gmail.com</email> (M.H.B.K.); <email>uroojalam109@gmail.com</email> (U.A.); <email>saadqazi@neduet.edu.pk</email> (S.A.Q.) 
700 1 |a Muhammad Hashir Bin Khalid  |u Neurocomputation Lab, National Center of Artificial Intelligence, Karachi 75270, Pakistan; <email>hashim@neduet.edu.pk</email> (H.R.K.); <email>majidakazmi@neduet.edu.pk</email> (M.K.); <email>lubabarehman16@gmail.com</email> (L.); <email>Mohammadhashirbinkhalid@gmail.com</email> (M.H.B.K.); <email>uroojalam109@gmail.com</email> (U.A.); <email>saadqazi@neduet.edu.pk</email> (S.A.Q.) 
700 1 |a Alam, Urooj  |u Neurocomputation Lab, National Center of Artificial Intelligence, Karachi 75270, Pakistan; <email>hashim@neduet.edu.pk</email> (H.R.K.); <email>majidakazmi@neduet.edu.pk</email> (M.K.); <email>lubabarehman16@gmail.com</email> (L.); <email>Mohammadhashirbinkhalid@gmail.com</email> (M.H.B.K.); <email>uroojalam109@gmail.com</email> (U.A.); <email>saadqazi@neduet.edu.pk</email> (S.A.Q.) 
700 1 |a Arshad, Kamran  |u Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman P.O. Box # 346, United Arab Emirates; <email>k.assaleh@ajman.ac.ae</email>; Artificial Intelligence Research Centre, Ajman University, Ajman P.O. Box # 346, United Arab Emirates 
700 1 |a Assaleh, Khaled  |u Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman P.O. Box # 346, United Arab Emirates; <email>k.assaleh@ajman.ac.ae</email>; Artificial Intelligence Research Centre, Ajman University, Ajman P.O. Box # 346, United Arab Emirates 
700 1 |a Saad Ahmed Qazi  |u Neurocomputation Lab, National Center of Artificial Intelligence, Karachi 75270, Pakistan; <email>hashim@neduet.edu.pk</email> (H.R.K.); <email>majidakazmi@neduet.edu.pk</email> (M.K.); <email>lubabarehman16@gmail.com</email> (L.); <email>Mohammadhashirbinkhalid@gmail.com</email> (M.H.B.K.); <email>uroojalam109@gmail.com</email> (U.A.); <email>saadqazi@neduet.edu.pk</email> (S.A.Q.); Faculty of Electrical and Computer Engineering, NED University of Engineering and Technology, Karachi 75270, Pakistan 
773 0 |t Sustainability  |g vol. 16, no. 10 (2024), p. 4137 
786 0 |d ProQuest  |t Publicly Available Content Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3059694486/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3059694486/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3059694486/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch