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Machine Learning Based Activity Learning for Behavioral Contexts in Internet of Things (IoT)

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Abstract

Ontology based activity learning models play a vital role in diverse fields of Internet of Things (IoT) such as smart homes, smart hospitals or smart communities etc. The prevalent challenges with ontological models are their static nature and inability of self-evolution. The models cannot be completed at once and smart home inhabitants cannot be restricted to limit their activities. Also, inhabitants are not predictable in nature and may perform “Activities of Daily Life (ADL)” not listed in ontological model. This gives rise to the need of developing an integrated framework based on unified conceptual backbone (i.e. activity ontologies), addressing the lifecycle of activity recognition and producing behavioral models according to inhabitant’s routine. In this paper, an ontology evolution process has been proposed that learns particular activities from existing set of activities in daily life (ADL). It learns new activities that have not been identified by the recognition model, adds new properties with existing activities and learns inhabitant’s newest behavior of performing activities through Artificial Neural Network (ANN). The better degree of true positivity is evidence of activity recognition with detection of noisy sensor data. Effectiveness of proposed approach is evident from improved rate of activity learning, activity detection and ontology evolution.

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Authors and Affiliations

  1. GC University Lahore Government College University, 54000, Lahore, Punjab, Pakistan

    Muhammad Safyan

  2. School of Engineering, London South Bank University, SE1 0AA, London, England

    Sohail Sarwar & Muddasar Iqbal

  3. Allama Iqbal Open University, H-8/2 H 8/2 H-8, 44000, Islamabad, Islamabad Capital Territory, Pakistan

    Zia Ul Qayyum

  4. Özyeğin University Nişantepe, Orman Sk. no. 13, 34794, Çekmeköy/İstanbul, Turkey

    Muhammad Kashif

  5. Unviersity of West of England UWE Bristol – Frenchay Campus, Coldharbour Ln, BS16 1QY, Bristol, UK

    Shancang Li

Authors
  1. Muhammad Safyan
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  2. Sohail Sarwar
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  3. Zia Ul Qayyum
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  4. Muddasar Iqbal
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  5. Shancang Li
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  6. Muhammad Kashif
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Correspondence to Muhammad Safyan, Sohail Sarwar, Zia Ul Qayyum, Muddasar Iqbal, Shancang Li or Muhammad Kashif.

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Safyan, M., Sarwar, S., Qayyum, Z.U. et al. Machine Learning Based Activity Learning for Behavioral Contexts in Internet of Things (IoT). Program Comput Soft 46, 626–635 (2020). https://doi.org/10.1134/S0361768820080204

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