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A platform for research: civil engineering, architecture and urbanism
Portable Construction Maps (PCM) using location fingerprint positioning algorithm for construction worker safety
The existence of a work from home policy does not seem to have a substantial impact on construction workers. Cases of work accidents on infrastructure projects during the Covid-19 pandemic experienced a significant increase. As reported by BPJamsostek data that the number of work accident insurance claims in the first semester (January-June) 2020 reached 108,573 cases. An increase of 128% over the same period in the previous year. One of the steps from the construction side to minimize the occurrence of work accidents is by marking dangerous locations or limiting them with a yellow line. The supervision is carried out by the Occupational Health and Safety division which supervises every worker by using hearing and sight senses. However, this supervision is deemed less effective and efficient considering the number of work accidents that continue to increase over time. Therefore, a worker location monitoring system based on An indoor positioning system called Portable Construction Maps (PCM) Using Location Fingerprint Positioning Algorithm for Construction Worker Safety was developed. The development of this system uses the algorithm Location Fingerprint as a method for estimating the location of workers in a construction building. Each worker will bring a device called the Worker Tag, in which there is a microcontroller (Espressif 32) with WiFi and Bluetooth module, which is used to capture wifi and bluetooth signals and calculate the Received signal strength indication(RSSI) which will be sent to the server to be processed using the location fingerprint algorithm. In addition, in the worker tag there is also a Passive Buzzer that is used to alert workers if they enter a dangerous area.
Portable Construction Maps (PCM) using location fingerprint positioning algorithm for construction worker safety
The existence of a work from home policy does not seem to have a substantial impact on construction workers. Cases of work accidents on infrastructure projects during the Covid-19 pandemic experienced a significant increase. As reported by BPJamsostek data that the number of work accident insurance claims in the first semester (January-June) 2020 reached 108,573 cases. An increase of 128% over the same period in the previous year. One of the steps from the construction side to minimize the occurrence of work accidents is by marking dangerous locations or limiting them with a yellow line. The supervision is carried out by the Occupational Health and Safety division which supervises every worker by using hearing and sight senses. However, this supervision is deemed less effective and efficient considering the number of work accidents that continue to increase over time. Therefore, a worker location monitoring system based on An indoor positioning system called Portable Construction Maps (PCM) Using Location Fingerprint Positioning Algorithm for Construction Worker Safety was developed. The development of this system uses the algorithm Location Fingerprint as a method for estimating the location of workers in a construction building. Each worker will bring a device called the Worker Tag, in which there is a microcontroller (Espressif 32) with WiFi and Bluetooth module, which is used to capture wifi and bluetooth signals and calculate the Received signal strength indication(RSSI) which will be sent to the server to be processed using the location fingerprint algorithm. In addition, in the worker tag there is also a Passive Buzzer that is used to alert workers if they enter a dangerous area.
Portable Construction Maps (PCM) using location fingerprint positioning algorithm for construction worker safety
Rasyid, Annurdien (author) / Firdaus, Ahsan (author) / Setiawan, Dwi (author) / Fitri, Hajidah Salsabila Allissa (author) / Setialana, Pradana (author) / Universitas Negeri Yogyakarta / Faculty of Engineering
2022-03-30
doi:10.21831/jeatech.v3i1.43666
Journal of Engineering and Applied Technology; Vol 3, No 1 (2022): (March); 27-34 ; 2716-2265 ; 2716-2257
Article (Journal)
Electronic Resource
English
DDC:
690
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