Department of Electrical and Electronics Engineering

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Author: search.filters.author.Shenoy, Meetha V.Subject: search.filters.subject.Neural networks

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    Sensor Information Processing for Wearable IoT Devices
    (Springer, 2019-11) Shenoy, Meetha V.
    Sensing technology is one of the core enablers of IoT and the improvement in sensing technology has lead to the proliferation of small form-factor, cost-effective and accurate sensors for wide variety of wearable applications. With wearable devices receiving widespread acceptance, their requirements are becoming more demanding, with the focus shifting from simple monitoring to context aware intelligent devices. This chapter presents a comprehensive description of the technical opportunities and challenges in the design of sensor information processing systems for wearables. A systematic survey of the state of the art architectures for sensor fusion for different application classes of wearable’s is presented. A discussion on design considerations for architecting sensor processing systems, including hardware, networking protocols, and algorithms at the edge, cloud level is provided. The chapter is concluded with a discussion on innovation directions in smart sensing and information processing in wearable devices.
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    Indoor localization in NLOS conditions using asynchronous WSN and neural network
    (IEEE, 2017) Shenoy, Meetha V.
    Development of technologies for accurate localization of objects in indoor environments can transform wide application domains like healthcare, warehouses and fitness industries. In this paper, we present a novel neural network and asynchronous wireless sensor network (WSN) based indoor localization scheme. A custom designed ultrasonic trans-receiver serves as the back bone of the localization scheme. In addition to the experiments on hardware, we utilize Locusim, an acoustic simulator to augument extensive analysis on Non line of Sight (NLOS) conditions. We demonstrate that the neural network based localization scheme can provide an accuracy suitable for most of the real world applications even under NLOS conditions.