SMART TOILET: Threats and Challenges Identifying Human Presence using IoT Sensors


Lokman, Amar and Ramasamy, R. Kanesaraj (2019) SMART TOILET: Threats and Challenges Identifying Human Presence using IoT Sensors. BDIOT 2019: Proceedings of the 3rd International Conference on Big Data and Internet of Things. pp. 56-60.

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This paper presents the design and implementation of an ultrasonic sensor and infrared sensor based on the presence of the human and the distance involved in the smart toilet, which is more and more popular in the real life. An ultrasonic sensor module (HC-SR04) is used to detect people at a certain distance, and Sharp GP2Y0A02YK0F analogue distance sensor is an infrared sensor to detect distance at a specific value. In the Smart Toilet, the height of each cubicle is about 236 centimeters for squatting toilets and 270 centimeters for the toilet bowl. When the person enters into each cubicle, the distance taken by the ultrasonic sensor will decrease from the default height. Body posture is the main challenge to the sensors because the sensor can provide more accurate result when the wave is reflected at the flat surface compared to the curved surface. Since the position of the human body is not flat, therefore the position of the sensor needs to be adjusted in order to get accurate measurements. We implemented a new method that can give a more reliable and accurate measurement for both sensors. This method includes technical specifications such as the wavelength of the wave, angle of the sensor, position of the sensor, the diameter of the detection space and last but not least the temperature of the surrounding. By using this technical specification, we could justify the exact distance of the sensor which can detect more accurately. Finally, we come out the suitability of the sensor that can be used inside the toilet.

Item Type: Article
Uncontrolled Keywords: Ultrasonic Sensor; Infrared Sensor; Raspberry Pi; Internet of Things (IoT); smart building.
Subjects: Q Science > QP Physiology > QP351 Neurophysiology and Neuropsychology
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 27 Oct 2021 04:40
Last Modified: 27 Oct 2021 04:40


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