Abstract-This paper discusses about an ongoing project that serves the needs of people with physical disabilities at home. It uses the Bluetooth technology to establish communication between user's Smartphone and controller board. The prototype support manual controlling and microcontroller controlling to lock and unlock home door. By connecting the circuit with a relay board and connection to the Arduino controller board it can be controlled by a Bluetooth available to provide remote access from tablet or smartphone. This paper addresses the development and the functionality of the Android-based application (Android app) to assist disabled people gain control of their living area.

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Due to its tasty and spicy fruit with nutritional qualities, chili is a demanding crop widely farmed around the world. Hence, it is essential to accurately determine the health status of chili for agricultural productivity. Recent years have seen impressive results in recognition fields due to deep learning approaches. However, deep learning models' networks need an abundant data to perform well and collecting enormous data for the networks is time-consuming and resource-intensive. A data augmentation method is proposed to overcome this problem. It was applied to a small dataset of healthy and diseased chili leaf by utilizing geometric transformation method. Eventually, two deep learning models of CNN and ResNet-18 were evaluated using augmented and original datasets. From a series of experiment, it can be concluded that the trained deep learning models using original and augmented datasets perform better with an average accuracy performance of 97%.

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