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Surveillance Enabled Smart Light with oneM2M Based IoT Networks

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Computational Intelligence, Communications, and Business Analytics (CICBA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 775))

Abstract

Electricity saved is electricity generated. On one side India has electricity deficit (38,138 million kWh during 2014–15 [1]), while on the other side, lots of electricity can be saved by converting existing lighting network in streets, campuses and houses into smart light. Geographic Information System (GIS) based software design can utilize these smart lights for surveillance. Hence in this paper conversion of existing lighting infrastructure to web based, centralized, surveillance enabled smart lighting has been proposed to reduce electricity wastage. The proposed solution involves hardware development for individual or cluster of lights, oneM2M enabled networking along with GIS based application software design for surveillance. The proposed solution has been demonstrated in field.

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Authors and Affiliations

  1. Centre for Development of Telematics, New Delhi, India

    Pankaj Kumar Dalela, Saurabh Basu, Smriti Sachdev, Sabyasachi Majumdar, Niraj Kant Kushwaha & Vipin Tyagi

Authors
  1. Pankaj Kumar Dalela
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  2. Saurabh Basu
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  3. Smriti Sachdev
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  4. Sabyasachi Majumdar
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  5. Niraj Kant Kushwaha
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  6. Vipin Tyagi
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Corresponding author

Correspondence to Saurabh Basu .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

  2. Department of Computer and System Sciences, Visva Bharati University, Bolpur Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Information Technology, Calcutta Business School, Kolkata, India

    Somnath Mukhopadhyay

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Dalela, P.K., Basu, S., Sachdev, S., Majumdar, S., Kushwaha, N.K., Tyagi, V. (2017). Surveillance Enabled Smart Light with oneM2M Based IoT Networks. In: Mandal, J., Dutta, P., Mukhopadhyay, S. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2017. Communications in Computer and Information Science, vol 775. Springer, Singapore. https://doi.org/10.1007/978-981-10-6427-2_24

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  • DOI: https://doi.org/10.1007/978-981-10-6427-2_24

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6426-5

  • Online ISBN: 978-981-10-6427-2

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