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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62030
Volume:
10 |
4 |
April 2026
Pages:
1-14
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Engineering and Technology
Sushant University
Engineering and Technology
Sushant University
Engineering and Technology
Sushant University
Engineering and Technology
Sushant University
As global urbanization places an unprecedented burden on water infrastructure, ensuring access to safe drinking water has become a critical challenge, as outlined in Sustainable Development Goal 6 (SDG 6). Current monitoring practices in water treatment environments often rely on manual sampling and laboratory analysis, leading to a "temporal delay" that prevents real-time responsiveness to contamination hazards. This paper proposes AquaHealth, an innovative, low-cost IoT solution designed to bridge the "accountability vacuum" and the "information gap" traditionally found in municipal water governance. This system utilizes a high-stability Arduino Uno architecture, which is comparatively demonstrated to be superior for real-time sensor stability when compared to higher-complexity dual-core chips like the ESP32. By integrating a turbidity sensor with a Python-based processing layer, the system performs real-time data analysis and visualization. AquaHealth employs a threshold-based classification logic, mapping sensor triggers to three distinct water safety statuses: Excellent, Fair, and Dirty. With a total implementation cost of approximately Rs. 1350, this research proves the feasibility of affordable "Transparency-as-a-Service" (TaaS) models for smart cities. By aligning with SDG 6, AquaHealth empowers citizens as auditors of their infrastructure, ensuring institutional accountability and safeguarding public health.
KEYWORDS
The development of AquaHealth has successfully demonstrated the feasibility of a portable, low-cost IoT system for real-time water quality monitoring, effectively bridging the gap between traditional manual testing and immediate data accessibility. By integrating a stable Arduino Uno architecture for precise analog sensing with a Python-based visualization layer, the system achieved consistent technical stability and eliminated signal noise, successfully automating water classification into "Excellent," "Fair," or "Dirty" categories via threshold-based logic. This integration allowed for live trend tracking and real-time analytics, providing a professional-grade monitoring tool on a minimal budget of Rs. 1314. Ultimately, AquaHealth contributes to the field by making high-stability monitoring accessible for community-level deployment, directly supporting Sustainable Development Goal 6 (Targets 6.1, 6.3, and 6.6) by transforming water safety data into a transparent, immediate resource for the end-user.
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Publication Date
4/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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