IOT News

I. Background and Challenges

As an important component of the urban ecosystem, the water quality of urban inland rivers is directly related to the living quality of urban residents and the health of the ecological environment. With the acceleration of urbanization, problems such as various types of domestic sewage and commercial wastewater have become increasingly serious, placing enormous pressure on water environment governance. Traditional inland river water quality monitoring mainly relies on manual periodic sampling and laboratory analysis, and this method has many drawbacks:

Poor timeliness: Manual sampling frequency is low and cannot reflect dynamic changes in water quality in real time, making it difficult to promptly detect sudden pollution incidents.
High labor costs: A large amount of manpower and material resources needs to be invested in sampling, transportation, and testing, resulting in low work efficiency.
Limited monitoring scope: It is difficult to achieve comprehensive monitoring of the entire inland river basin and multiple points, and pollution points are easily missed.

II. Solution

In order to achieve real-time, comprehensive, and accurate monitoring of inland river water quality and improve the level of urban water environment management, it is imperative to introduce IoT technology to build an urban inland river water quality monitoring IoT system. In response, a solution for an urban inland river water quality monitoring IoT system based on industrial intelligent gateways is provided. It mainly consists of the following parts:

Perception layer: Composed of various water quality monitoring sensors distributed at different locations in the inland river, such as pH sensors, dissolved oxygen sensors, turbidity sensors, ammonia nitrogen sensors, and chemical oxygen demand (COD) sensors. These sensors collect various parameters of inland river water quality in real time and transmit the data to the industrial intelligent gateway.

Transmission layer: With the industrial intelligent gateway as the core, it is responsible for transmitting the data collected by the perception layer to cloud servers through communication methods such as 4G/5G. The gateway has data caching and breakpoint resume functions. When the network is unstable, it can temporarily store data and automatically resend it after the network recovers, ensuring data integrity.

Platform layer: A water quality monitoring and management platform is built on the cloud server, responsible for receiving, storing, and managing data transmitted from the gateway. The platform implements functions such as real-time monitoring of water quality conditions, trend prediction, and abnormal alarms. At the same time, the platform also provides a data visualization interface, displaying inland river water quality information in intuitive charts, maps, and other forms, making it convenient for management personnel to view and make decisions.

III. Implemented Functions

Real-time monitoring: The system can collect various parameters of inland river water quality in real time and quickly transmit them to the cloud platform, achieving 24-hour uninterrupted monitoring. Users can view the current real-time status of inland river water quality at any time, such as pH value, dissolved oxygen content, turbidity, and pollutant concentration, and grasp water quality change dynamics in a timely manner.

Data storage and management: Efficiently store and manage the large amount of collected water quality data, and establish a complete database. Data storage adopts a redundant backup mechanism to ensure data security and reliability. At the same time, it provides functions such as classified query and statistical analysis of data, making it convenient for users to retrieve and analyze historical data according to conditions such as time, location, and parameters.

Abnormal alarms: The system can compare and analyze real-time monitoring data according to set water quality indicator thresholds. When water quality parameters exceed the normal range, the system immediately automatically triggers the alarm mechanism and sends alarm information to relevant management personnel through various methods such as SMS, email, and WeChat, reminding them to take timely measures to respond to pollution incidents and reduce environmental pollution risks.

Data analysis and prediction: Using big data analysis and artificial intelligence algorithms, conduct in-depth mining of long-term accumulated water quality data, and analyze the change trends, seasonal characteristics, and correlations with surrounding environmental factors of inland river water quality. By establishing water quality prediction models, predict water quality changes in advance, provide decision-making basis for water environment management departments, and achieve scientific water governance and precise policy implementation.

Visualized display: The water quality monitoring and management platform provides an intuitive and rich visualization interface, displaying inland river water quality information through various forms such as maps, charts, and curves. On the electronic map, the locations and water quality conditions of each monitoring point are marked in real time, with different colors identifying the degree of water quality superiority or inferiority, allowing management personnel to grasp the overall water quality distribution of the inland river at a glance.