Noise Attenuation on IMU Measurement for Drone Balance by Sensor Fusion

Stability is the key to maintain and control the drone, which is challenged by significant noise from drone motors during operation. The paper presents the Kalman filter and Complementary filter based on the quaternion to optimize drone stability. An exponential moving average (EMA) filter is used to minimize the significant vibration noise inside angular rates. The designed models optimize the misleading data from the Inertial Measurement Unit (IMU) sensor on the drone caused by noise. A real test bench was constructed to verify the proposed methods. An MPU 6050 (triaxial accelerometer and triaxial gyroscope) is equipped with a Racing Drone; then, the sensor data is logged in a MicroSD Card for signal analysis. The results demonstrate that the Complementary filter attenuates variation due to the noise, but it has an issue with drift. On the other hand, the Kalman filter accomplishes more stable output surrounding the drone's balanced point

Body temperature—indoor condition monitor and activity recognition by mems accelerometer based on IoT-alert system for people in quarantine due to COVID-19

Coronavirus disease 19 (COVID-19) is a virus that spreads through contact with the respiratory droplets of infected persons, so quarantine is mandatory to break the infection chain. This paper proposes a wearable device with the Internet of Things (IoT) integration for real-time monitoring of body temperature the indoor condition via an alert system to the person in quarantine. The alert is transferred when the body thermal exceeds the allowed threshold temperature. Moreover, an algorithm Repetition Spikes Counter (RSC) based on an accelerometer is employed in the role of human activity recognition to realize whether the quarantined person is doing physical exercise or not, for auto-adjustment of threshold temperature. The real-time warning and stored data analysis support the family members/doctors in following and updating the quarantined people’s body temperature behavior in the tele-distance. The experiment includes an M5stickC wearable device, a Microelectromechanical system (MEMS) accelerometer, an infrared thermometer, and a digital temperature sensor equipped with the user’s wrist. The indoor temperature and humidity are measured to restrict the virus spread and supervise the room condition of the person in quarantine. The information is transferred to the cloud via Wi-Fi with Message Queue Telemetry Transport (MQTT) broker. The Bluetooth is integrated as an option for the data transfer from the self-isolated person to the electronic device of a family member in the case of Wi-Fi failed connection. The tested result was obtained from a student in quarantine for 14 days. The designed system successfully monitored the body temperature, exercise activity, and indoor condition of the quarantined person that handy during the Covid-19 pandemic