The sensor nodes of existing wireless sensor systems require actively generated radio frequency electromagnetic waves for data transmission, which leads to high power consumption. Passive wireless sensor systems that use backscattering modulation technology require high-cost dedicated readers, which results in limited applications. To solve these problems, this article proposes an ultra-lowpower wireless sensor system that manipulates the Wi-Fi channels. The designed system modulates the sensing data into the signals transmitted by the Wi-Fi device using backscattering modulation, which affects the parameters of the Wi-Fi channels. The system achieves ultra-low-power wireless sensing without a dedicated reader by using a Wi-Fi receiving device to obtain channel state information and training a machine learning detector capable of demodulating sensing data through the support vector machine. The wireless temperature sensing system is established using a router, a wireless network card, and a wireless sensor node. The maximum power consumption of the wireless sensor node is less than 350 μW. The Wi-Fi receiving device that employs a wireless network card can read the sensing data transmitted at 200 bit / s when the wireless sensor node is within 5 m of the router. The system provides an effective solution and satisfies the demand for ultra-low-power wireless sensors in smart homes, wearable devices, and other applications.