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DC Field | Value | Language |
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dc.contributor.author | Susithra, N. | - |
dc.contributor.author | Santhanamari, G. | - |
dc.contributor.author | Deepa, M. | - |
dc.contributor.author | Reba, P. | - |
dc.contributor.author | Ramya, K. C. | - |
dc.contributor.author | Garg, Lalit | - |
dc.date.accessioned | 2023-05-19T15:33:04Z | - |
dc.date.available | 2023-05-19T15:33:04Z | - |
dc.date.issued | 2021 | - |
dc.identifier.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. | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/109621 | - |
dc.description.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. | en_GB |
dc.language.iso | en | en_GB |
dc.publisher | Springer International Publishing | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Deep learning (Machine learning) | en_GB |
dc.subject | Internet of things | en_GB |
dc.subject | Information technology | en_GB |
dc.subject | Smart cities | en_GB |
dc.title | Deep learning-based activity monitoring for smart environment using radar | en_GB |
dc.title.alternative | Challenges and solutions for sustainable smart city development | en_GB |
dc.type | bookPart | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.description.reviewed | peer-reviewed | en_GB |
dc.identifier.doi | 10.1007/978-3-030-70183-3 | - |
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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