Vývojář: Amrita Vishwa Vidyapeetham (19)
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Gel-IoT
To understand community-specific water quality index, it is not enough to have data based on water quality parameters only. An increase in anthropogenic activity, population growth, and urbanization have a significant impact on all natural resources, particularly water quality, which is worsening. Along with all of these scenarios, extreme variability in weather patterns aggravates the situation by exponentially increasing the crisis to the access, availability, and affordability of clean drinking water solutions. This is becoming a major concern and crisis. Another major challenge is not having access to real-time information on dynamic variability in water contamination levels and its impact on public health, which contributes to a lack of awareness among multiple stakeholders. Hence multiple stakeholders are not able to ensure safe drinking water availability since they lack real-time knowledge of dynamical geo-spatial variation of water quality and its impact. Therefore, climatic variations along with the terrain and environmental factors lead to a dynamic spatio-temporal impact on regional water quality. Indeed the above challenges have prompted us to study all the Water Quality Index (WQI) impact factors such as terrain features, climatic variations, anthropogenic activities, agricultural practices, etc., that affect the water quality and develop a solution that could determine dynamically varying zonal water quality indices. Water quality variability of different sources will be studied by employing multiple data monitoring techniques such as remote sensing, in-situ monitoring, and so on. The GEL-IoT framework is capable of disseminating the data captured using such monitoring techniques and thereby empowering the community members and other stakeholders to be ‘water-wise’. It enables the identification of the predominant contaminants, and the diseases caused by them which the water authority or decision-makers could use to take corrective measures for a specific location. All the information collected by the GEL-IoT framework will aid the design and development of AI-based decision models integrating the geospatial models (GeoAI models) and community-centric business models which helps in the sustainability of the water purification system and formation of water-wise communities.
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#1. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham
#2. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham
#3. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham
#4. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham
#5. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham
#6. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham
#7. Gel-IoT (iOS) Podle: Amrita Vishwa Vidyapeetham

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  • Verze: 2.0.1
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