In the last decades, monitoring cameras begin to play a vital role in securing sensitive systems such as government sites or establishments. Generally, these kinds of cameras are fixed-location (i.e. outdoor camera) such that the viewpoint is limited to small area and not covering the whole place. In addition, there are some drawbacks that appear when using these kinds of cameras such as being breakable (intentionally or not) which may lead to camera malfunction or breaking in the linked electrical wires that may cause disconnection between the camera, monitor and its receiver. However, the main problem is the lacking of secure protecting system that prevents intruders from entering into the system disabling or malfunction it. In this research a new system is proposed in order to solve these problems by using wireless-mobile camera with embedded programmable operating system which enables controlling this camera remotely by sending wireless commands through the embedded component called Arduino card controller. This card enables the connection between the camera and the server to be programmatic by the user or developer. The main goal of this research is to design a monitoring system to detect any suspicious events and to ensure that the transferring monitoring data from the camera to the server is not infiltrated by unauthorized person by applying a set of techniques from image detection, object tracking and security algorithms to the instructions or the program of the camera. Compared with other researches, this work achieved the following goals: 1- Using Arduino card for programming the camera. 2- IP camera does not require user name and password. 3- The images and the other information are (encrypted) when sending to/from computer, 4- Using Mobile-wireless camera. 5- Process of keys exchanging between camera and computer. The results of this research are good and achieved the main goals of new developed technique.
Plant diseases have a negative impact on the agricultural sector. The diseases lower the productivity of the production yield and give huge losses to the farmers. For the betterment of agriculture, it is very essential to detect the diseases in the plants to protect the agricultural crop yield while it is also important to reduce the use of pesticides to improve the quality of the agricultural yield. Image processing and data mining algorithms together help analyze and detection of diseases. Using these techniques diseases detection can be done in rice leaves. In this research, the image processing technique is used to extract the feature from the leaf images. Further for the classification of diseases various machine learning algorithm like the random forest, J48 and support vector machine is used and the result is compared among different machine learning algorithm. After model evaluation, classification accuracy is verified using the n-fold cross-validation technique.
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