Today, technology has been developing rapidly. Various types of technology have been developed and provide a great deal of convenience in human life activities, including security systems. Motorcycles, parked in a park or on the street, are at high risk of being stolen. A security system for Motorcycles with SMS warning and GPS tracking that can prevent theft of a motorcycle is needed. The research aimed to design a security system for motorcycle consisting of a SIM808 GSM Module to send warning messages, and a GPS tracker to provide information in latitude and longitude coordinates to track the stolen motorcycle using Google Maps. GPS Tracker worked by reading the coordinates where the object was located. The tests were carried out by moving and integrating the motorcycle system, and the results could be seen in the coordinate changes, monitored by Google map showing the movement of the motorcycle. The system made was significantly closer to what was planned.

Face tracking is important system for robotic. The problem is that it is less resistant to occlusion and noise. Robust face tracking algorithm in this paper using improved mean shift algorithm is proposed. This algorithm consist of face detection and tracking. The face identification is done by the Viola-Jones algorithm. Then, Mean Shift algorithm is done to track face as a target and improve robustness from occlusion. CBWH is added in face as target to reduce noise. The experimental results prove that it is robust from noise background and occlusion..

Air pollution caused by exhaust emission of motor vehicles especially the two wheels contain a wide range of harmful gases that can cause disease. Therefore, emission tests are indispensable in controlling the emissions of gas that are loose into the air. However, not many people know the importance of emission testing. In addition to the emission results can not store periodic data, the available emission test devices are also very limited. Therefore, the author proposes the feasibility “Test Monitoring system for motorised vehicles with Arduino-based Internet of Things”. In data retrieval use a simple linear regression method. In this tool the x-axis is the ADC value of the sensor while the y-axis is the value of gas levels. The greater the ADC value, the greater the PPM value is generated. Emission test data storage using the Internet of Things method. The Data that has been saved can be viewed through websites and Android apps. After several tests, there were 3.05% error percentage for HC gas and 3.91% for CO gas and data could be stored in the database. Overall this tool is worthy of use to measure the exhaust emissions of motorised vehicles.

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