Sewerage overflow monitoring system based on Internet of Things technology solves sewer overflow

Recently, Silicon Labs (also known as "core technology") Duo Zhang (Zhang Wei) of the Oslo office in Norway published a book entitled "Use Long Short-Term Memory to Enhance Internet of Things" in the international authoritative academic journal 'Journalof Hydrology' For Combined Sewer Overflow Monitoring' (using the long- and short-term memory to enhance the Internet of Things for sewer overflow monitoring). The article explains how to collect and build data models through Silicon Labs' advanced IoT technology and then use it to improve urban drainage problems, and further implement the concept of IoT applications.

The Internet of Things is booming, and more connected devices are being incorporated into the Internet of Things, which will be a catalyst for data explosion. In this case, how to analyze and utilize the collected data in an intelligent way has become the key to the next development of the Internet of Things. In fact, Silicon Labs has long noticed the trend of the Internet of Things from 'object' to 'big data,' as shown below:

In the Drammen drainage system upgrade project in Duo Zhang, Norway, engineers built a sewer overflow monitoring system based on IoT technology. Sewer overflow refers to the situation where excess sewage overflows from the pipe network overflow facility when the amount of sewage exceeds the carrying capacity of the sewage pipe network, and is discharged to the water body without treatment. Sewer overflow is one of the main sources of pollution in water bodies, and it is also an urgent problem to be solved in drainage systems. In order to strengthen the control of sewer overflow, it is necessary to establish a precise time series model based on the data collected by the Internet of Things.

To this end, Mr. Duo Zhang used a variety of artificial intelligence to establish a time series model based on rainfall data collected from the Internet of Things and sewer water level data, including the most traditional Multilayer Perceptron, a wavelet commonly used in hydrological research. Wavelet Neural Network, and the most advanced Deep Leaning technology, such as Long Short-term Memory, Gated Recurrent Unit.

Deep learning is currently a hot topic, and AlphaGo, which recently defeated the World Champion of Go, is one of the representative applications of deep learning. Long-term and short-term memory is currently the most widely used means of natural language processing, and Google's latest neural machine translation system uses this technology. Mr. Duo Zhang's experiments show that the deep learning method is superior to the traditional method in both single-step prediction and multi-step prediction, and the deep learning method can effectively reduce the problems of hysteresis and peak oscillation in traditional time series prediction.

It is reported that 'Journal of Hydrology' is a top journal certified by the Chinese Academy of Sciences. It was first published in 1963 and is one of the earliest hydrological academic journals. It is highly prestigious in many fields such as water resources, engineering and geosciences. Mr. Duo Zhang pointed out that the receipt of articles in such high-quality journals means that the Internet of Things and artificial intelligence technologies have attracted the attention of mainstream academics. Mr. Duo Zhang predicts that technologies such as the Internet of Things and artificial intelligence will break through the barriers of the electronics and computer industries and extend their reach to a wider field. This trend will greatly change or even subvert many traditional industries. This aspect means that the traditional engineering community needs to be prepared for danger and actively absorb new technologies. On the other hand, it also indicates that the new blue ocean market will open for us and bring huge scientific and commercial value. We hope that Silicon Labs' advanced IoT technology can be combined with artificial intelligence technology to contribute to creating a smarter world.