Abstract
According to Robert McSweeney, in light of a new study: “Conditions in the GCC could become so hot and humid in the coming years that staying outside for more than six hours will become difficult”. He is a climate analyst at CARBON BRIEF, a nonprofit temperature and climate analysis group. He also states that changes there can help give us an idea of what the rest of the world can expect if we do not reduce the emissions that pollute homes and factories. Because of the high temperatures in GCC countries, the effect of heat stress is very high there, which discourages shoppers and pedestrians from shopping in the open area due to the physical exertion and high risks faced by people and workers. Heat stress peaks in most Arab Gulf countries from 11:00 a.m. to 4:00 p.m. during the summer season. Heat stress is increasingly an obstacle to economic efficiency in these countries. This work designs and develops a robot that tracks shoppers and provides a cool stream of air directly around them during shopping in open areas to reduce the effect of heat stress. The robot enables us to cool the temperature around customers in the market to increase comfort. In this project, a robot was designed and manufactured to track a specific person and cool the air around him through a cool stream of air generated by the air conditioner installed inside the robot. We used a Raspberry Pi camera sensor to detect the target person and interact with a single-board computer (Raspberry Pi 3) to accomplish this design and the prototype. Raspberry Pi controls the air-conditioning robot to follow the movement of the target person. We used image processing to discover the target shopper, the control system, and then guide the bot. In the meantime, the robot must also bypass any potential obstacles that could prevent its movement and cause a collision. We made a highly efficient design that can synchronize between the software algorithm and the mechanical platform of the robot. This work is merely the combination of a cool stream of air and a robot that follows a human.
Highlights
Yousif et al [1] asserted that, due to the significant rise in temperatures, several cities in the GCC region, such as Jeddah, Dubai, Oman, and Doha, classify as having a desert climate
If we extend the lines that form the field of view (FOV) angle inside the camera into the real world, it is easy to determine the angular limits of our video camera
We conduct image masking, which returns a binary matrix by considering the range of the color. image_mask = cv2.inRange (HSV, low, high) If we conduct a logical mask with the original images, we can see the image with the defined color
Summary
Yousif et al [1] asserted that, due to the significant rise in temperatures, several cities in the GCC region, such as Jeddah, Dubai, Oman, and Doha, classify as having a desert climate. We use the jacket as a marker for target shopper detection This system performs image processing for noising object subtraction, jacket identification, the position and distance between the air-conditioner robot and shopper determination, and tracking a specific shopper. We focus on developing a human-tracking intelligent robot to improve the high efficiency following system and provide a relaxing atmosphere for shoppers. To perform this task accurately, we need a mechanism to visualize the moving object and act . The image processing algorithm for specified color detection was developed under a Python environment for reducing noise in the background of the moving object (the shopper).
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