Design and simulation of an automated bacteria detection and water treatment system for water safety distribution.

Abstract

Abstract Ensuring safe water distribution is critical for public
health, requiring efficient real-time monitoring and treatment of
bacterial contamination. Manual water quality monitoring and
treatment are typically performed at weekly or monthly intervals,
making them inefficient and allowing bacteria to grow unchecked
between tests, potentially reaching end-users and exposing
communities to health risks. To address this challenge, this study
presents the design and simulation of an automated bacteria
detection and treatment system that integrates light-based
absorption and transmission sensing, control mechanisms,
and ultraviolet (UV) disinfection technology. The methodology
involved modeling bacterial growth using a logistic equation and
simulating system responses in MATLAB/Simulink. The detection
module provided real-time bacterial concentration data, which
triggered appropriate disinfection actions. The UV disinfection
unit was simulated to evaluate its efficiency, achieving > 99%
bacterial reduction within 30 seconds of UV-C exposure at an
intensity of 7 mW/cm2
. Results demonstrated that the system
effectively detected bacteria in real-time, with photodiode voltage
dropping from 15 V to below 10 V as bacterial concentration
increased, and recovering after disinfection. Automation reduced
response time and improved water quality consistency compared
to traditional monitoring and treatment methods. Significantly,
these results demonstrate a scalable engineering framework
for decentralized water infrastructure; by replacing periodic
manual assays with automated optical-to-valve control loops,
this architecture provides an actionable roadmap for real-time
pathogen mitigation in aging municipal grids and domestic
holding tanks, ultimately reducing waterborne disease outbreaks
in resource-constrained communities. Overall, the study confirms
that an automated bacteria detection and treatment system can
significantly enhance water safety through real-time monitoring
and adaptive disinfection, offering a scalable solution for
improving public health and reliability of water distribution
systems.