In the era of Intelligent IoT, huge amount of sensor data is collected and then transmitted to processor elements in edge devices or cloud servers. The latency and energy consumption in this process have been a bottleneck and are becoming more severe. To mitigate this problem, the idea of combining sensors, memory and processors for collectively handling the data, has been proposed and explored actively in recent efforts. In this work, thin-film transistor (TFT), which has been widely adopted in display devices and flexible sensors, is exploited. It is shown that, while TFT is promising for near-sensor processing architecture, it also shows a great potential for computing and storing data for large-area and low-cost edge sensors. More specifically, we propose an almost-nonvolatile near-sensor computing-in-memory (CiM) array based on IGZO TFT, and further, integrate the CiM array with a sensor array to be a sensing and data pre-process system. We show that such a TFT-based solution can accomplish real-time sensing and multiply-and-accumulate (MAC) processing in the analog field, which simplifies the system design with lowered energy and latency in our neural network evaluations.