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Communication and Computation Inter-Effects in People Counting Using Intelligence Partitioning
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
2020 (English)In: Journal of Real-Time Image Processing, ISSN 1861-8200, E-ISSN 1861-8219Article in journal (Other academic) Epub ahead of print
Abstract [en]

The rapid development of the Internet of Things is affecting the requirements towards wireless vision sensor networks (WVSN). Future smart camera architectures require battery-operated devices to facilitate deployment for scenarios such as industrial monitoring, environmental monitoring and smart city, consequently imposing constraints on the node energy consumption. This paper provides an analysis of the inter-effects between computation and communication energy for a smart camera node. Based on a people counting scenario, we evaluate the trade-off for the node energy consumption with different processing configurations of the image processing tasks, and several communication technologies. The results indicate that the optimal partition between the smart camera node and remote processing is with background modelling, segmentation, morphology and binary compression implemented in the smart camera, supported by Bluetooth Low Energy (BLE) version 5 technologies. The comparative assessment of these results with other implementation scenarios underlines the energy efficiency of this approach. This work changes pre-conceptions regarding design space exploration in WVSN, motivating further investigation regarding the inclusion of intermediate processing layers between the node and the cloud to interlace low-power configurations of communication and processing architectures.

Place, publisher, year, edition, pages
2020.
Keywords [en]
Intelligence partitioning, Smart camera, WVSN, Energy-efficiency, IoT, In-sensor processing
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:miun:diva-37177DOI: 10.1007/s11554-020-00943-6Scopus ID: 2-s2.0-85078090728OAI: oai:DiVA.org:miun-37177DiVA, id: diva2:1349830
Note

An initial manuscript version of this article was included in the licentiate thesis.

Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2020-02-21Bibliographically approved
In thesis
1. Intelligence Partitioning for IoT: Communication and Processing Inter-Effects for Smart Camera Implementation
Open this publication in new window or tab >>Intelligence Partitioning for IoT: Communication and Processing Inter-Effects for Smart Camera Implementation
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The Internet of Things (IoT) is becoming a tangible reality, with a variety of sensors, devices and data centres interconnected to support scenarios such as Smart City with information about traffic, city administration, health-care services and entertainment. Decomposing these systems into smaller components, results in a variety of requirements for processing and communication resources for each subsystem. Wireless Vision Sensor Network (WVSN) is one of the subsystems, relying on visual sensors that produce several megabytes of data every second, unlike temperature or pressure sensors producing several bytes of data every hour. In addition, to facilitate the deployment of the nodes for different environments, we consider themas battery-operated devices. The high data rates from the imaging sensor have extensive computational and communication requirements, which in the meantime should meet the constraints regarding the energy efficiency of the device, to ensure a satisfactory battery lifetime.

In this thesis we analyse the energy efficiency of the smart camera, including the smart camera architecture, the distribution of the image processing tasks between several processing elements, and the inter-effects of processing and communication. Sensor selection and algorithmic implementation of the image processing tasks affects the processing energy consumption of the node, alongside to the hardware and software implementation of the tasks.

Furthermore, considerations of different intelligence partitioning configurations are included in the analysis of communication related elements, such as communication delays and channel utilisation. The inter-effects resulting from the variety of configurations in image processing allocation and communication technologies with different characteristics provide an insight into the overall variations of the smart camera node energy consumption. The aim of thesis is to facilitate the design of energy efficient smart cameras, while providing an understanding of energy consumption variations related to processing and communication configurations.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2019. p. 54
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 152
National Category
Embedded Systems
Identifiers
urn:nbn:se:miun:diva-37178 (URN)978-91-88527-85-1 (ISBN)
Presentation
2019-01-17, O102, Sundsvall, 10:00 (English)
Supervisors
Projects
SMART (Smarta system och tjänster för ett effektivt och innovativt samhälle)
Note

Vid tidpunkten för framläggningen av avhandlingen var följande delarbete opublicerat: delarbete 3 (manuskript).

At the time of the defence the following paper was unpublished: paper 3 (manuscript).

Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2019-09-10Bibliographically approved

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Shallari, IridaKrug, SilviaO'Nils, Mattias

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