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This innovative project aims to monitor water quality in the area of continental, the coast and the lake using mobile buoy remotely controlled by a computer which sends a series of commands to Intel Atom N2600 Board and microcontrollers over Global System for Mobile Communication (GSM). The user enters the desired coordinate to Graphical User Interface (GUI) monitoring software from a remote computer. The buoy moves to the desired coordinate that relies on Global Positioning System (GPS) current reading. Sets of data of PH, Oxidation Reduction Potential (ORP) and temperature sensors reading is taken from sensors attached at the buoy. The data and the coordinate of the buoy location is uploaded and mapped via Google Map. The Google Map is integrated into the GUI to display the buoy position. The user can freely monitor real-time water quality information and the buoy will go to any location coordinated by the user's command.

Nowadays, it is hard to distinguish the type of orchid leaf diseases just by using naked eyes. This paper presents an image segmentation technique for classify two difference types of orchid leaf disease such as black leaf spot and sun scorch. The orchid leaves images were digitally captured by using digital camera. With respect to the region of interest selected orchid leaves are analyze by using border segmentation techniques using MATLAB. In this paper, filtering technique and morphological processing technique will be applied to the images. The graphical user interface has been developed to automatically classify orchid diseases. The system has potential as early detection system for classify orchid diseases.Index Terms-image segmentation, morphological techniques, black leaf spot, sun scorch 978-1-4799-6106-

Stem measurement is vital since its diameter is related to development of tree as well as water content. Hence, in this study, PIC microcontroller based instrumentation is developed for measuring the changes of linear micrometer that represents the stem diameter changes. Here, the strain gauge is used as a sensor to detect the changes in micrometer for every 1μm changes. In addition, digital multimeter and digital oscilloscope are used for comparison and validation of the proposed PIC. Results attained proven that the system is capable to measure changes of stem diameter accurately.

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