The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time via Pattern Recognition


  • Marhaini M.S. Faculty of Computer System and Software Engineering Universiti Malaysia Pahang, Malaysia.
  • Mohamed Ariff Ameedeen Faculty of Computer System and Software Engineering Universiti Malaysia Pahang, Malaysia. BM Centre of Excellence, Universiti Malaysia Pahang, Malaysia


Classification, Extreme Learning Machine (ELM), Food Calorie, Pattern Recognition, Ultra-Mobile Near Infrared (NIR) Spectrometer,


Calories refer to a unit of energy that people should consume based on total energy needed. Thus, a system for health monitoring applications that can measure calories and nutrition can be very useful. This research is mainly focused on creating a new algorithm based on classification technique to calculate food calorie intake in real-time. Enhancement on Extreme Learning Machine (ELM) algorithm will be done to get better results in terms of accuracy and speed of calculating the food calorie. The ELM algorithm will be applied to an ultramobile Near Infrared (NIR) spectrometer. While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. The results will display the total amount of calories consumed per day, per week and per month with total amount of calories left in a mobile application


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How to Cite

M.S., M., & Ameedeen, M. A. (2016). The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time via Pattern Recognition. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(6), 103–107. Retrieved from