BLUETOOTH BASED INDOOR LOCALIZATION IN HOUSES FOR PEOPLE WITH SEVERE DEMENTIA USING TRILATERATIUON ALGORITHM

• Main Author: Zaid Abdurrahman, Diaz
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/73695
• Institution: Institut Teknologi Bandung

Localization within the house is one of the studied subjects because the implementation of such technology is extensive and flexible, including the localization of people with dementia inside the house. In Indonesia alone, the number of elderly individuals is around 30 million and will grow exponentianally by 2050. This large number of elderly individuals is correlated to the increasing number of elderly individuals with dementia. To assist families with dementia patients, the author has developed a device capable of tracking elderly individuals within a single-story house. Tracking the elderly is an effort to stimulate their mental and physical well-being, which is crucial in reducing the degeneration of individuals with dementia. Therefore, the author will assemble a device that can track the elderly, alleviating family concerns when they are away from home engaging in other activities. The author will build a receiver or subsystem that captures signals from transmitters in the form of beacons. This subsystem will process the received signals from multiple beacons to generate two-dimensional coordinate outputs. These coordinates are calculated using the trilateration algorithm, which utilizes simple trigonometric calculations with three beacon radius to determine the x and y coordinates. The transmitter subsystem will also communicate with a website using WiFi to provide the calculated data for visualization on the website. The expected scenario is that individuals with dementia will wear the transmitter, enabling their tracking inside the house. The tracking results can be accessed by users outside the house, allowing them to view the location on a house floor plan visualization with predefined dimensions. The implementation of the self-made subsystem will be done on a PCB using a microcontroller as the brain and signal receiver from the beacons. The microcontroller will be programmed to perform its intended functionalities such as reading RSSI signals, connecting to WiFi, and performing calculations. Overall, the final project meets the predetermined specifications, although some aspects may not fully meet the indicators. The achieved tracking accuracy is within the range of 1.7m - 2.2m with a latency of 20 seconds. The lack accuracy or latency could be caused by calculation errors during the utilization of the trilateration algorithm or signal interference from the same frequency.