An IoT-Based Water-Logging Detection System for Dhaka, Bangladesh

核心概念

An IoT-based system to continuously monitor water level, flow, and gas levels in drainage pipes to detect and alert authorities about water-logging issues in Dhaka, Bangladesh.

摘要

The content discusses the problem of water-logging in Dhaka, Bangladesh, and proposes an IoT-based solution to address it.
Key highlights:

Dhaka, the capital of Bangladesh, faces severe water-logging issues due to heavy rainfall, clogged drainage pipes, and poor maintenance of the sewerage system.
The proposed system uses IoT sensors to continuously monitor water level, flow, and gas levels in drainage pipes. This data is sent to a central database and displayed on an operator dashboard.
The system can detect potential water-logging issues by analyzing the sensor data and send alerts to the nearest maintenance office.
The hardware prototype includes a Node MCU microcontroller, GPS module, water flow sensor, ultrasonic sensor, and gas sensor.
The system uses a four-layer architecture: perception layer (sensors), network layer (wireless communication), data link layer (database), and application layer (operator dashboard).
The simulation results show the system can effectively detect and alert about water-logging problems in the drainage system.

統計資料

The average annual rainfall in Bangladesh is 200 mm per year.
Dhaka has faced more rainfall than ever before in recent years.

引述

"Water-logging is a major problem that many cities face. It is quite common in cities of third world countries, especially those countries that are bestowed with the season of monsoon like Dhaka, Bangladesh."
"Lack of basic education and sanitation sense has caused people to clog up drainpipes. Criminals are also to blame for water-logging; they are illegally encroaching the waterbodies that serve the city."

從以下內容提煉的關鍵洞見

An IoT Based Water-Logging Detection System

by Md Manirul I... 於 arxiv.org 03-29-2024

https://arxiv.org/pdf/2403.18949.pdf

深入探究

How can the proposed system be expanded to cover a larger area of Dhaka or other cities in Bangladesh?

To expand the proposed system to cover a larger area of Dhaka or other cities in Bangladesh, a scalable approach can be adopted. This would involve deploying additional sensor nodes strategically across the city to monitor water levels, flow rates, and gas levels in drainage pipes. The system can be designed to be modular, allowing for easy integration of new sensor nodes as needed. Utilizing a wireless communication network, such as LoRa or NB-IoT, can facilitate seamless data transmission over long distances, enabling comprehensive coverage of a larger area. Additionally, incorporating a centralized dashboard for monitoring multiple sensor nodes simultaneously would enhance the system's scalability.

What are the potential challenges in implementing this system, such as cost, maintenance, and user adoption?

Several challenges may arise in implementing the proposed system. Cost can be a significant factor, as deploying IoT sensors, setting up a network infrastructure, and maintaining the system can incur expenses. Ensuring regular maintenance of the sensors and network components is crucial to prevent system failures. User adoption may also pose a challenge, as educating the local population about the system's benefits and encouraging their active participation in waste management practices can be a complex task. Addressing privacy and data security concerns related to collecting and storing sensitive information from the sensors is another challenge that needs to be carefully managed.

How can the data collected by this system be leveraged to improve urban planning and infrastructure development in Dhaka?

The data collected by the IoT-based water-logging detection system can be leveraged to enhance urban planning and infrastructure development in Dhaka in several ways. By analyzing the real-time water level, flow rate, and gas level data, city authorities can identify areas prone to water-logging and prioritize infrastructure upgrades in those locations. This data can also be used to optimize drainage system maintenance schedules, leading to more efficient resource allocation. Furthermore, historical data analysis can provide insights into long-term trends and patterns, enabling informed decision-making for future urban development projects. Integrating this data with geographic information systems (GIS) can facilitate spatial analysis and visualization, aiding in the identification of high-risk areas for water-logging and guiding urban planning initiatives.