Infrared detection technology is widely used in the field of chemical engineering, bio-medicine, food safety, among the many chemical substance detection techniques due to its characteristics such as non-destructiveness, high sensitivity, fast detection speed, and good accuracy. Quantum dot (QD) spectrometer is a new type of micro spectrometer that uses QD instead of grating as a light splitting device and combines array detector with spectral reconstruction algorithm to realize spectrum detection. It has the advantages of small size and low cost. In order to improve the universality of existing QD spectrometers, QD devices for detecting chemical substances, and ultimately provide an effective technical approach for the development of micro-near infrared (NIR) spectroscopy devices. This article used hazardous chemicals Ethanol, simulants of chemical warfare agent sarin, mustard gas, including Dimethyl Methylphosphonate and Dichloromethane as the targets. A NIR colloidal quantum dot (CQD) array with an emission spectrum of 900~1 600 nm was prepared by mixing a variety of QD materials with UV curing glue and deposited on the RGB dot matrix. Extracted the high-frequency signal of the input spectrum and reduced the random noise interference with empirical mode decomposition method, established the corresponding spectrum reconstruction algorithm based on the least square method. The experimental results show that the preparation method of the NIR CQD array is simple, low-cost, and stable. The reconstructed spectral resolution achieved by the NIR CQD array with 144 spectral channels can reach 4.861nm. Compared with the standard absorption spectrum, the minimum deviation of its characteristic peak is only 0.043%. Therefore, detecting and identifying gas and liquid targets can be achieved by combing the NIR CQD arrays with spectral reconstruction algorithms. In the future, the spectral resolution of the reconstructed spectrum can be effectively improved by increasing the number of arrays; Spectral detection from UV to IR can also be achieved by increasing the QD materials selected; Target detection signal-to-noise ratio can be improved by optimizing the optical detection path and the reconstruction algorithm parameters.