\begin{abstract}

In a IoT environment, many devices will periodically transmit data. However, most of the data are redundant, but sensor itself may not have a good standard to decide send or not. Some static rule maybe useful on specific scenario, and become ineffective when we change the usage of the sensor. Hence, we design an algorithm to solve the problem of data redundant. In the algorithm, we iteratively separate an image into some smaller regions. Each round, choose a region with highest variability, and separate it into four regions. Finally, each region has different size and uses its average value to represent itself. If an area is more various, the density of regions will be higher. In this paper, we present a method to reduce the file size of thermal sensor which can sense the temperature of a surface and outputs a two dimension gray scale image. In our evaluation result, we can reduce the file size to $50\%$ less than JPEG when $0.5\%$ of distortion, and up to $93\%$ less when there is $2\%$ of distortion.

\end{abstract}
