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Zhi-Hao Wang
Southern Taiwan University of Science and Technology
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Electric vehicle power monitoring system based on IoT sensing architecture Jia-Syuan Lin; Zi-Fang Tsai; Zhi-Hao Wang; Hendrick
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (705.455 KB)

Abstract

At present, most of the vehicles in life are mainly based on gasoline and diesel, and with the gradual advancement of vehicle technology, but also accelerating global warming, countries have launched a variety of green energy to reduce the harm to the earth. Many vehicles have been developed into hybrid vehicles, and a large number of pure electric vehicles have been launched in recent years. On the other hand, many countries have begun to plan carbon footprint and carbon allowance management, and the emission of greenhouse gases or the use of green energy will be more regulated in the future. Therefore, this research will take the electric stacker as the test target, measure the values of current and voltage, input the measured values into the program to calculate the carbon emissions produced during operation, and obtain the carbon emissions emitted by driving electric vehicles that are significantly smaller than the carbon emissions emitted by driving gasoline and diesel vehicles.
Driving Physiological State Monitoring Based on IoT Sensing Architecture Yi-Ching Kuo; Yu-lian Yu; Zhi-Hao Wang; Hendrick
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1033.055 KB)

Abstract

In clinical practice, alcoholic beverages will have imaging effects on the autonomic nervous system. Common reactions of the human body after absorbing alcohol include unsteady walking, rapid heartbeat, and reddening of the face. In this case, humans are usually unable to fully rely on self-consciousness to manipulate the body, and consciousness tends to become blurred. In recent years, the incidents of drinking and driving have emerged in an endless stream. Although there are laws and regulations, they cannot effectively prevent and control drunk driving. Therefore, this study intends to develop an alcohol lock that can monitor the physiological state of driving. The architecture proposed in this study uses the pulse oximeter to obtain the PPG signal and then analyzes the autonomic nervous system and uses the MQ-3 alcohol sensor to detect the air alcohol content in the cockpit. The two signals are sensed by ESP32 and sent to the base station outside the car by LoRa through the IoT architecture. Finally, the driving physiological information will be sent to the server for centralized display
Co-Authors - Hendrick Jia-Syuan Lin Yi-Ching Kuo Yu-lian Yu Zi-Fang Tsai