Ahmed Sohaib

Zain Mumtaz, Zeeshan Ilyas, Ahmed Sohaib et al.

Our proposed system has seven main contributions, i.e., Smart street lights, Smart home, Bio-metric door and home security system, Intelligent traffic lights management and road security system, Private and smart parking, Intelligent accident management system and Smart information display/ notice board system. Our prototypes / products employ Arduino UNO board, Node MCU, Ultrasonic sensor, Fingerprint module, Servo motors, GSM, GPS, LEDs, Flame Sensor, Bluetooth and Wi-Fi module etc. We are very confident that our proposed systems are efficient, reliable, and cost-effective and can be easily tested and implemented on a large scale under real conditions.

Muhammad Hussain Khan, Zainab Saleem, Muhammad Ahmad et al.

Preserving red-chili quality is of utmost importance in which the authorities demand the quality techniques to detect, classify and prevent it from the impurities. For example, salt, wheat flour, wheat bran, and rice bran contamination in grounded red chili, which typically a food, are a serious threat to people who are allergic to such items. This work presents the feasibility of utilizing visible and near-infrared (VNIR) hyperspectral imaging (HSI) to detect and classify the aforementioned adulterants in red chili. However, adulterated red chili data annotation is a big challenge for classification because the acquisition of labeled data for real-time supervised learning is expensive in terms of cost and time. Therefore, this study, for the very first time proposes a novel approach to annotate the red chili samples using a clustering mechanism at 500~nm wavelength spectral response due to its dark appearance at a specified wavelength. Later the spectral samples are classified into pure or adulterated using one-class SVM. The classification performance achieves 99% in case of pure adulterants or red chili whereas 85% for adulterated samples. We further investigate that the single classification model is enough to detect any foreign substance in red chili pepper rather than cascading multiple PLS regression models.