The RainVest

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Published Oct 10, 2021
Sarang Krishnakumar Mishra Dr. Swati Hira Gauri Kulkarni Ruqaiya Dargahwala Palash Jhanwar Abbas Hussain

Abstract

Currently, people install water storage tanks separately per building/apartment for roof top rainwater harvesting, which results in a significant expense for individuals/groups. No mechanism/application is available to find out where such installations are beneficial, which installations can share storage tanks and what would be the required capacity of these shared tanks.  Shared Rainwater Harvesting System will make proper use of water storage spaces, eliminating the need for fossil fuels or electric-driven pumping technology and offers protection against flooding. Scope of rainwater harvesting not only depends on the quality of rainfall but also the area available for storage is a concern since in future there will be barely free land available so the main problem will occur due to confined areas. That is why we aim to develop a system that offers an alternative decentralized water source especially in the age when the groundwater supplies are depleting and municipal water infrastructure is facing high replacement costs. As this is a sustainable project, it will replenish our water table only at a one-time investment. As modernization and development of technology boon the future there will be a possibility that we might get cheaper filter technology which cleans the rainwater completely and make it for consumption use, which will boost the rainwater harvesting system.

Rainwater harvesting has been used in India for over 4000 years. It is just a simple technique of collecting and storing rainwater. Rainwater harvesting devices have been used as a source of drinking water, irrigation water, and animal water since prehistoric times. In traditional methods, collecting is often done with the assistance of infrastructure, or the most basic technique for a rainwater harvesting system is storage tanks. In this case, a water catchment region is directly linked to cisterns, tanks, and reservoirs. Water can be stored here until it is needed, or it can be utilised on a regular basis.

This traditional method discussed above has some drawbacks like unpredictable rainfall, initial high cost, regular maintenance and storage limits.Our project offers an alternative decentralized water source especially in the age when the groundwater supplies are depleting and municipal water infrastructure is facing high replacement costs. As this is a sustainable project, it will replenish our water table only at a one-time investment. It will help to find out where such installations are beneficial. The project aims to provide the modern approach of rain water harvesting.

Using map and housing data provided by the user, this model will provide the cost benefit analysis justifying the plan. The machine learning aspect of our project is used to estimate the dimensions of the roof (OpenCV and Computer Vision Models) along with rainfall estimation. Open Computer Vision is a graphical image processing library known for better processing of lower to higher resolution of images. Considering the case of India, getting high resolution satellite images for different inert areas is extremely difficult and thus needs a lot of preprocessing which is much easier and faster to carry out in OpenCV.

 

 

 

 

The main objective of the technology is :

Estimating rainwater harvesting capacity:

  1. Rainfall estimation: Historical data from rainfall gauges at different places in the target area.
  2. Catchment area: Masterplan of the city to estimate the catchment area available, e.g open areas like rooftop, courtyard, etc
  3. Provide a cost benefit analysis justifying the plan.

This modern approach covers the main drawbacks of traditional methods.

 

How to Cite

Sarang Krishnakumar Mishra, Dr. Swati Hira, Gauri Kulkarni, Ruqaiya Dargahwala, Palash Jhanwar, & Abbas Hussain. (2021). The RainVest. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/2379
Abstract 60 |

Article Details

Keywords

Satellite Image, OpenCV, Ra, Rainfall Prediction, Depth Estimation

References
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Section
SF2: Ecological Restoration: Land and Underwater

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