Characterization of Pattern for Predicting Ultra Violet (UV) Effects in Environment Data Management System (EDMS)

• Main Authors: M. Amir Abas, M. Dahlui, UniKL BMI
• Language: English
• Published: 2013
• Subjects: Pattern; Monitoring; Measurement; Recognition; Formulation
• Online Access: http://ir.unikl.edu.my/jspui/handle/123456789/5210
• Institution: Universiti Kuala Lumpur

This paper presents the development of analysis tools for predicting ultra violet (UV) effects through statistical pattern recognition technique. The increasing phenomena of UV level in many areas have severe implications especially to the weather and on the people. An effective measurement system; Environment Data management System (EDMS) had been designed to monitor the UV level so that preventive and control measures could be taken up. This system is capable of measuring, processing and analyzing the environment data. Data will be processed through analysis tools, utilizing the statistics pattern recognition technique. The pattern recognition was executed by comparing the month to month or year to year measurement data. The performance of the system in measuring the effect of high UV to the environment had been evaluated in a case study, whereby the monitoring of UV and its effects had been conducted at Rawang. Rawang was chosen for its rapid development which had changed its status from the green tropical area to the polluted semi-industrial area. Her relatively big population size, many new housing estates, many vehicles and factories, and several construction sites had contributed to the climax change. The measurement system EDMS could integrate all these factors to analyze the effect and subsequently can be used to relate with the current weather and recent human disease especially skin cancer and eye cataract. The result of the measurement exercises produced various patterns, each with unique identification for developing database pattern algorithm. Statistical analysis graph was plotted to justify the one year measurement of UV, temperature and humidity.