| Autor: |
Rajasi Gore, Shashwati Banerjea, Neeraj Tyagi |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Advances in Intelligent Systems and Computing ISBN: 9789811627118 |
| DOI: |
10.1007/978-981-16-2712-5_34 |
| Popis: |
Public toilets are being established in India to make it an open-defecation free country. These amenities are assigned workers to monitor its cleaning. Due to negligence, improper usage, and lack of timely maintenance, majority of them are in bad condition. There is a critical requirement of an Internet of Things (IoT)-based smart application to automate the monitoring of these public toilets and provide services. This work proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based IoT application for smart monitoring of large-scale public amenities. Determining a toilet state is fuzzy as the condition of toilet is affected by multiple factors such as environmental conditions, day and hour of usage, rate of usage and type of use. ANFIS is used as an information fusion model to predict the amenity state and determine an action accurately. Dampster–Shafer theory is implemented to reduce the data uncertainty in the input feature set of the ANFIS model. A real prototype-based experiment confirmed the effectiveness of the proposed information fusion model. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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