\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 to 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 for IoT devices. In the algorithm, we iteratively separate a data region 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 has more dynamical diverse data, 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 is allowed, and up to $93\%$ less when $2\%$ of distortion is allowed.

\end{abstract}
