Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/109621
Title: | Deep learning-based activity monitoring for smart environment using radar |
Other Titles: | Challenges and solutions for sustainable smart city development |
Authors: | Susithra, N. Santhanamari, G. Deepa, M. Reba, P. Ramya, K. C. Garg, Lalit |
Keywords: | Deep learning (Machine learning) Internet of things Information technology Smart cities |
Issue Date: | 2021 |
Publisher: | Springer International Publishing |
Citation: | Susithra, N., Santhanamari, G., Deepa, M., Reba, P., Ramya, K. C., & Garg, L. (2021). Deep learning-based activity monitoring for smart environment using radar. In R. Maheswar, M. Balasaraswathi, R. Rastogi, A. Sampathkumar, G. R. Kanagachidambaresan (Eds.), Challenges and Solutions for Sustainable Smart City Development (pp. 91-123). Cham: Springer International Publishing. |
Abstract: | It is evident from the advent of various technological advancements including IoT that smart cities determine the nation’s future in terms of economic salvation, resource management, connectivity across the nation, optimum reach of all the utilities to the nook and corner of the country, environmental safety, and societal safety, and the list is endless. This aspiration has kindled a growing interest among the entrepreneurs, engineers, and investors in taking part in the race to build smart cities. Smart cities demand development of sustainable monitoring systems for all kinds of environments. Urbanization, sustainable development, and inclusive growth necessitate the efficient and intelligent utilization of natural resources for a better living. |
URI: | https://www.um.edu.mt/library/oar/handle/123456789/109621 |
Appears in Collections: | Scholarly Works - FacICTCIS |
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Deep_learning_based_activity_monitoring_for_smart_environment_using_radar_2021.pdf Restricted Access | 1.27 MB | Adobe PDF | View/Open Request a copy |
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