The advancement of technology, make robots have more attention from researchers to make life of mankind comfortable. This paper deals with the design of an itemized control system prepared for window cleaning/maintenance of towers and multistory buildings which can be aided to simulating human activities. These activities (washing, coating, wiping, climbing, and maintenance events) normally achieved by specialized personal. The designed control system was prepared to guide the units of the required job to move freely along the outside surface of a window with a fairly enough area and mediate time for achieving the desired goal. The system design is implemented using Arduino kit, due to facilities in program and control of cleaning windows through infer the stepper motor movement and rotation. The controller has been achieved as real time system (30 msec.), it is done throw control of three stepper motor by taken in consideration the speed of the motors (π/3000 rad/sec) and the time can be adjustable within the cleaning area that the device covering it.

<span lang="EN-US">There are some medicines and medical treatments that need to be injected into the human body through the blood vessels, and this requires placing the cannula in the patient’s body. The blood vessels in the human body differ from one person to another, and medical personnel face major problems in finding the blood vessels in most cases, because of The difference in skin color, where it is difficult to see the blood veins in the skin with black pigment, and it is difficult to find it in people with obesity because of the layers of fat, and in children and newborns because these veins are small. This study talks about finding a way to photograph these veins, see them by design and implementation low cost prototype used equipment that were recycled old device, such as a web camera, infrared lamps and overhead device, All of these devices are of low cost. Then process these images using binary image, histogram equalization, segmentation and threshold to detect these blood veins. The algorithms for edges images detecting are many and complex, this study used five methods to detect vein image, such as Sobel, Laplacian, Canny, Roberts, and Prewitt.</span>