Search Results - "Manivannan, Ajaykumar"

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  1. 1

    On the Challenges and Potential of Using Barometric Sensors to Track Human Activity by Manivannan, Ajaykumar, Chin, Wei Chien Benny, Barrat, Alain, Bouffanais, Roland

    Published in Sensors (Basel, Switzerland) (27-11-2020)
    “…Barometers are among the oldest engineered sensors. Historically, they have been primarily used either as environmental sensors to measure the atmospheric…”
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  2. 2

    Effects of the interplay between topology and function of an integrated urban development on patterns of user movement by Manivannan, Ajaykumar, Chin, Wei Chien Benny, Gopalakrishnan, Srilalitha, Wong, Daniel K. H., Schroepfer, Thomas, Bouffanais, Roland

    Published in Scientific reports (25-03-2024)
    “…With the advent of distributed multi-sensory networks of devices, vast troves of real-time data can be gathered about our interactions with the built…”
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  3. 3

    A Framework for the Identification of Human Vertical Displacement Activity Based on Multi-Sensor Data by Manivannan, Ajaykumar, Willemse, Elias J., B. T, Balamurali, Chin, Wei Chien Benny, Zhou, Yuren, Tuncer, Bige, Barrat, Alain, Bouffanais, Roland

    Published in IEEE sensors journal (15-04-2022)
    “…To date, the methodology to track and identify vertical movement from large-scale unstructured data sets is lacking. Here, we design and develop such a…”
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  4. 4

    Are the different layers of a social network conveying the same information? by Manivannan, Ajaykumar, Yow, W. Quin, Bouffanais, Roland, Barrat, Alain

    Published in EPJ data science (15-09-2018)
    “…Comprehensive and quantitative investigations of social theories and phenomena increasingly benefit from the vast breadth of data describing human social…”
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  5. 5

    Are the different layers of a social network conveying the same information? by Manivannan, Ajaykumar, Yow, W. Quin, Bouffanais, Roland, Barrat, Alain

    Published 09-01-2018
    “…EPJ Data Science 7 (2018) 34 Comprehensive and quantitative investigations of social theories and phenomena increasingly benefit from the vast breadth of data…”
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    Journal Article