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Image Storage and Broadcast via Bluetooth Low Energy Beacons: Demo Abstract

Published: 18 April 2017 Publication History

Abstract

This demo is an implementation of the first 'image beacon' system that can broadcast color images over the years. We developed the system using a set of cheap, low-power, memory-constrained Bluetooth Low Energy (BLE) beacon devices. The system integrates an image processing pipeline. In order to achieve the best quality image under a very strict size limit, the pipeline takes into account the background and foreground information of an image and then applies an adaptive encoding method that encodes an image by prioritizing more important regions of the image. We develop a Raspberry Pi application for image writing. It takes an image and user-requirements as inputs, shows previews of different quality output images, writes the encoded image into a set of beacons. We also develop a smartphone application that reads the broadcasted image from beacons. In practice, the system can broadcast image data for years without external power supply.

References

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Tianyu Lu, Zisheng Le, and DYY Yun. 2000. Piecewise linear image coding using surface triangulation and geometric compression. In Data Compression Conference, 2000. Proceedings. DCC 2000. IEEE, 410--419.
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Shahriar Nirjon and John A Stankovic. 2012. Kinsight: Localizing and tracking household objects using depth-camera sensors. In 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems. IEEE, 67--74.
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Amir Said and William A Pearlman. 1996. A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on circuits and systems for video technology 6, 3 (1996), 243--250.
[4]
Chong Shao, Shahriar Nirjon, and Jan-Michael Frahm. 2016. Years-Long Binary Image Broadcast using Bluetooth Low Energy Beacons. In Proceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS 2016).
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Jerome M Shapiro. 1993. Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on signal processing 41, 12 (1993), 3445--3462.

Cited By

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  • (2018)Demo Abstract: Image Storage and Broadcast over BLE with Deep Neural Network Autoencoding2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2018.00050(302-303)Online publication date: May-2018

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cover image ACM Conferences
IoTDI '17: Proceedings of the Second International Conference on Internet-of-Things Design and Implementation
April 2017
353 pages
ISBN:9781450349666
DOI:10.1145/3054977
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 April 2017

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Author Tags

  1. Bluetooth beaconing
  2. image processing

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  • (2018)Demo Abstract: Image Storage and Broadcast over BLE with Deep Neural Network Autoencoding2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2018.00050(302-303)Online publication date: May-2018

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