Hello, I am looking for someone to write an article on Adaptive Sampling in Wireless Sensor Network. It needs to be at least 3750 words. This detection strategy is based on an extension to the Holts Method and statistical model. To investigate this strategy, water consumption in a household is used as a case study. A number of performance metrics are used to evaluate the adaptive sampling strategy, including sampling fraction, missing ratio, and sampling performance. The experimental results show that the proposed strategy over-performs compared to two existing sampling algorithms.Wireless sensing systems has recently become a topic of interest to many researchers, especially in terms of in-network data collection. Wireless sensor networks (WSN) are considered one of the reliable environmental monitoring systems that are constructed using various techniques and numerous algorithms, which are studied and analyzed according to the deployment plan. Courtesy of its targeted sensing accuracy cost reduction, and energy consumption, the technology has been used in studies and experiments that have been conducted and implemented with great precision. Although many researchers are continuously working in this field, it appears less than satisfactory for the rapid development and technological improvements of the future. For example, for event detection. adaptive sampling is used to balance the sample rate when an abnormal behavior or event in the collected data is detected.This paper addresses the problem of capturing the essential details from the measurement of household water temperature while minimizing the energy consumption of the sensor’s battery. The existing adaptive sampling techniques proposed for data acquisition have critical limitations. particularly the concern of energy consumption. Hence, we propose an adaptive sampling algorithm based on time-series statistics and the concept of TCP Reno congestion control. Our approach is designed to generate data from the source node only when a significant change is detected.