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A heterogeneous soft-hard fusion framework on fog based private SaS model for smart monitoring of public restrooms

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Abstract

Usage of public restrooms, provided by the Indian government under “Clean India Mission”, is limited due to negligence in manual supervision. This paper proposes an Internet of Things-based smart application for sanitation to keep check on geographically distributed restrooms autonomously through soft-hard sensors. Due to a substantial increase in the number of sensing devices in recent years, the application aims to re-utilize data from hard sensors co-located near the restroom locations. A private Sensing as a Service (SaS) paradigm is proposed on the fog node that provides sensor data as a service at the network edge to reduce new sensor deployments. The data from re-utilized sensors is vendor-specific, and, therefore, have heterogeneous protocols and file formats, unknown to the application vendor. A soft-hard fusion framework is proposed to handle data heterogeneity of re-utilized data and perform time-series fusion of hard-sensor data (vendor-specific or application-specific) with uncertain soft sensor data at the fog node for having complete and accurate information about the toilet. The proposed framework takes approximately 0.145 s to resolve heterogeneity, handle soft uncertainty and perform fusion with low resource consumption. Moreover, it has a good system as well as network performance with increased classification accuracy in predicting the cleaning requirement of every toilet.

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Data Availability

The datasets generated during and/or analysed during the current study are available in the GitHub repository, https://github.com/RajasiG/soft-hard-fusionDataset.git.

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Funding

This work is fully funded by the Ministry of Education (MoE), Government of India.

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Authors and Affiliations

  1. Computer Science and Engineering Department, MNNIT Allahabad, Prayagraj, Uttar Pradesh, 211004, India

    Rajasi Gore, Shashwati Banerjea & Neeraj Tyagi

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  1. Rajasi Gore
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  2. Shashwati Banerjea
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  3. Neeraj Tyagi
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Correspondence to Rajasi Gore.

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Gore, R., Banerjea, S. & Tyagi, N. A heterogeneous soft-hard fusion framework on fog based private SaS model for smart monitoring of public restrooms. J Ambient Intell Human Comput 14, 8957–8984 (2023). https://doi.org/10.1007/s12652-022-04401-y

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