Muhamad Komarudin

Smart monitoring of electrical quantities based on single board computer BCM2835

Electricity network needs to be monitored, especially for Voltage (V) measurement, current (A), power factor (cos θ), power (W), and energy consumption (kWh). Monitoring is important, in order to know the quality of electricity supply in the system, identifying disruption events, and to calculate the amount of electrical energy consumption periodically. To achieve the objectives mentioned above, we have made device that can be monitor the electrical quantities in real time, recorded data was stored in to database system, and web application processed this data and shown the statistic reports through a web interface. This research was conducted on the 3 phase electricity at The Integrated Laboratory of the Electrical Engineering Department University of Lampung. Monitoring of voltage, current and energy consumption was done by using a step-down transformator as a voltage sensor, ACS712-30A as current sensors for capture the flow measurement, and TEM015-D4250 kWh meter for measuring energy consumption. Power and Power Factor value was obtained by some of scientific calculation. We used Python programming language for data processing measurement and calculation, running on BCM2835 Single Board Computer. The results of measurements include voltage, current, power factor, power, and the amount of energy consumption was stored in to data base, and data report can be accessed online using web browser.

Study of environmental condition using wavelet decomposition based on infrared image

In this paper, we report our experiment about wavelet decomposition for study environmental condition based on infrared images. Infrared images acquired by consumer digital camera, after replacing the infrared stoping filter with filter SRS, and the images captured sequentially every two hours (from 06:00-16:00). The result of this research is the increasing air pollution characterized using wavelet decomposition by increasing index value from 0-3 and amount of white spots about 60% (from 5%-65%). Finally wavelet decomposition was made to estimate the environmental condition, especially air pollution, based on infrared image.

Intensity average value of image segmentation for infrared image of environmental condition

In this paper, we make a report our research about intensity average value of image segmentation for infrared image of air pollution. Infrared image of environmental condition (captured sequentially every two hours, from 06:00-16:00) processed using wavelet transform. After that processed, used image segmentation to get intensity average value distribution from 0 till 255 to obtain trending graphic of pollution. Infrared image divided into 4, 8, and 16 segments. The result of this research is the increasing air pollution characterized at 12:00 and 16:00, by increasing intensity average value from 13%-27%. Finally intensity average value of image segmentation was made to estimate the environmental condition, especially air pollution, based on infrared image.