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

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.