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Person Localization in an Indoor Environment with Artificial Intelligence

Published: 19 April 2019 Publication History

Abstract

Associative models are Artificial Intelligence tools and have been used in many applications such as pattern recognition, classification, encryption, among others. In this paper we applied these models to trace a person in an indoor environment by the means of the power of a Wi-Fi signal. We deal with this problem as a classification task. We used a preprocessing for the data to improve the results. Our performance was 95.75%.

References

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Rohra, J.G., Perumal, B., Narayanan, S.J., Thakur, P., Bhatt, R.B. User Localization in an Indoor Environment Using Fuzzy Hybrid of Particle Swarm Optimization and Gravitational Search Algorithm with Neural Networks. In: Deep K. et al. (eds) Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 546. Springer, Singapore.
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    ICCAI '19: Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence
    April 2019
    267 pages
    ISBN:9781450361064
    DOI:10.1145/3330482
    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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    Published: 19 April 2019

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    Author Tags

    1. Artificial Intelligence
    2. Associative Models
    3. Classification
    4. Indoor Environment
    5. Pattern Recognition
    6. User Localization

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