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Tareq Khan

Eastern Michigan University

Author-ID : 2377862

Computer Science & IT Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document

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Articles

Smart Microwave Oven with Image Classification and Temperature Recommendation Algorithm Tareq Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

When food is warmed in a microwave oven, the user guesses the estimated time for the heating. This cognitive process of guessing can be incorrect - resulting the final food temperature to be too hot or still cold. In this research, a novel closed-loop microwave oven is designed which automatically suggests the target temperature of a food by learning from previous experiences and the heating stops automatically when the food temperature reaches the target temperature. The proposed microwave captures and classifies the food image, and recommends the target temperature, thus the user does not need to remember the target food temperature each time the same food is warmed. The algorithm gradually learns the type of foods that are used in that household and becomes smarter in the recommendation. The proposed algorithm can recommend target temperature with an accuracy of 86.31% for solid food and 100% for liquid food. A prototype of the proposed microwave is developed using the embedded system and tested.

Low Complexity Fluctuation Measurement in Image Processing Considering Order Tareq Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

The standard deviation can measure the spread out of a set of numbers and entropy can measure the randomness. However, they do not consider the order of the numbers. This can lead to misleading results where the order of the numbers is vital. An image is a set of numbers (i.e. pixel values) that is sensitive to order. In this paper, a low complexity and efficient method for measuring the fluctuation is proposed considering the order of the numbers. The proposed method sums up the changes of consecutive numbers and can be used in image processing applications. Simulation shows that the proposed method is 8 to 33 times faster than other related works.

A noninvasive smart wearable for diaper moister quantification and notification Tareq Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

A baby feels uncomfortable in a wet diaper and it can cause health issues such as diaper rash. Diaper rash can be avoided by changing the diaper as soon as the baby urinates or passes stool. In this project, a smart wearable gadget is developed which sends an automatic notification to a caregiver’s smartphone whenever the baby urinates. The proposed wearable detects urination event noninvasively by sensing the temperature rise on the outer surface of the diaper and quantifies the event using a decision tree and a midpoint based k-nearest neighbor (KNN) hybrid classification algorithm. The gadget is a small size, low power, low cost and reusable electronic device that is attached externally to the outer surface of the diaper. The gadget can be used with any disposable diaper, thus no change in the diaper production process or price increase is required. The smartphone app shows the diaper change urgency score and logs all the urination events. This record can facilitate treating diseases where accurate records of urination are required. A prototype of the hardware gadget and a smartphone app is developed and tested.

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