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Journal : Proceeding International Applied Business and Engineering Conference

Object Detection And Monitor System For Building Security Based On Internet Of Things (IoT) Using Illumination Invariant Face Recognition Ivan Chatisa; Yoanda Alim Syahbana; Agus Urip Ari Wibowo
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.688 KB)

Abstract

Theft, burglary and intrusion are criminal acts that often occur in the environment when there are opportunity or negligence made by the owner and security officers. Many studies have been carried out to improve environmental security by applying cameras as a surveillance medium. However, the camera is still not optimal at detecting objects if the environment is in poor lighting conditions (dark). Therefore, in this study, a monitoring and object detection system was built by applying the Illumination Invariant model. Illumination Invariant model that is used to improve the appearance of object images from light and shadow reflections. In this study, the detection process and objects are carried out using human facial features captured by the camera. The camera used is a Logitec C270 Webcam HD 720p via the USB port on the Raspberry Pi. Raspberry Pi processes human face image data and sends the results of data processing to a MySQL database using the HTTP Protocol. The process of sending data is done with the concept of API (Application Programming Interface) using Python Flask. In this study, all tests were carried out on the system using black box testing techniques with the results of the functional requirements being successfully executed 100%. In this study, testing the object detection feature based on different lighting conditions. The test was carried out 15 times by comparing the original image and the results of the implementation of the Illumination Invariant model. Based on the test results by applying the illumination of the Invariant model, the quality of object detection accuracy is 86.7%.
Peat Soil Temperature Monitoring System With IoT Technology Hatta Zulkifli; Agus Urip Ari Wibowo; Memen Akbar
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1307.762 KB)

Abstract

Peat soil is a soil element that is very susceptible to burning if it is dry and when burned peat will be synonymous with giving rise to dense smoke and giving rise to embers. Prevention has been carried out so far by building a monitoring tower to see the condition of a peatland from a certain height, but because this is done by humans, there will certainly be limitations in monitoring quickly and precisely. By utilizing the development of Internet of Things technology, a solution that can be done by building a system called Silahan Gambut (SILAGA), where this system has been tested on peatlands using the DB18S20 sensor calibrated with a DHT 22 sensor Using Internet of Things technology, it has been successfully monitored in real time the condition of a peatland that has the potential to burn. The results of the sensor data are managed using MongoDB noSQL so that the data obtained is well managed on peat soils at a certain time, condition and region.
Hotpoint Monitoring System Power Cable Termination Based On Internet of Things (IoT) Using Telegram Bot Muhammad Syahri; Agus Urip Ari Wibowo; Dadang Syarif Sihabudin Sahid
International ABEC Vol. 2 (2022): Proceeding International Applied Business and Engineering Conference 2022
Publisher : International ABEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1926.812 KB)

Abstract

Electricity is energy that is needed in any field, both industry and ordinary people. To be able to produce good quality electrical energy, it is necessary to monitor and maintain electrical power equipment to prevent equipment damage that can interfere with the electrical energy distribution system to consumers. One of the disturbances that are often experienced is the Hotpoint at the terminal connection section between the conductor cable and the equipment at the substation. Hotpoint is an increase in the production of acoustic pulses (sound) and an increase in temperature that causes energy dissipation resulting in the heating of a localized area. This Hotpoint will cause damage to the equipment if it occurs for a long time. In this research, a Hotpoint monitoring system for 20 kV power cable termination based on the Internet of Things was built to monitor the temperature condition of the 20 kV power cable termination in real-time. This system uses the MLX90640 IR Thermal Camera sensor as the cable termination temperature gauge and the DHT22 temperature sensor to measure the 20 kV cubicle panel temperature. This temperature value will be compared to determine whether there is a Hotpoint at the termination of the 20 kV power cable. This system uses a MySQL database and HTTP protocol for communication between the Raspberry Pi4 and the website dashboard, then for notifications using the Telegram bot. The sensor accuracy test is carried out by comparing the temperature value between the DHT22 sensor and the Hygrometer with an average measurement value difference of -1.7%, while the MLX90640 and Fluke Ir 568 sensor accuracy tests have an average measurement value difference of -1.13%°C. Based on the sensor accuracy testing, it can be concluded that all sensors have a fairly good performance in measuring the required temperature parameters.