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A WiFi technology was the basis of the Internet of Things (IoT) and many popularity of the wireless communication in the social network. A smart device used any kinds of the detectors all of the analog and digital sensor. This study simulates on the scope of the home security system (HSS). There used three types of sensor; a temperature sensor, smoke-CO, and PIR sensor. This study aims to design a multi-sensor node. All of the sensors are connected on a microcontroller unit (MCU) with the general purpose input output (GPIO). After the connection, there got invalid multi-sensor data. This experiment tried to run over ten times. There appeared some invalid when the processor startup. First, the temperature sensor did not work. Second, the smoke-CO sensors read an invalid value there were higher than the actual. This problem can solve the situation by the sensor calibration methodology—to set the calibration time with the dynamic time follow up on the GPIO function of each sensor and self-calibrate by the finite impulse response (FIR) filter in the part of setup portion. When the system was running for a long time this should take the invalid data. There were high and low from the actual and there got the difference value suddenly a swinging value. During the system was running there had some noise and the heat collected on the device. There got the invalid value. This error is solved by the Full Scale Kalman Filter (FSKF) to fill and estimate the right value. Next, there used the OFF-Mode to save the power consumption and do not send sensor data to the Cloud all time. This method helps the device will be run as long time and work in long life. Finally, there got a high-performance WiFi multi-sensor network.

Cloud Based WiFi Multi-Sensor Network