Health is one the most vital aspects that is of greater concern to most of the human beings at present days. To keep people healthier they intake a lot of fruits which contains more amount of nutrition and helps them to remain fit. Health benefits are provided with the intake of fruits and people who regularly intake fruits are expected to have minimized risk of chronic diseases. The Nutrients provided by the fruits are vital for proper maintenance of the body. But those fruits nowadays are ripened through some artificial means like usage of chemicals like calcium carbide as ripening agent which might even cause cancer. An important news that flashes during the mango seasons in television is that the fruit markets contain artificially ripened fruits which is extremely hazardous to health. Artificial ripening of mangoes using calcium carbide was the important fact that was being displayed in the news. Despite repeated warnings, raids and seizures, chemically ripened fruits are flooding the market. According to health officials, the consumption of mangoes ripened using calcium carbide leads to various harmful effects like vomiting, diarrhoea, ulcers of throat and abdomen, general weakness, and sometimes damage of eye permanently and breathing shortness. To avoid such ill effects the consumers have to be careful in buying the mangoes, find out the artificially ripened mangoes. Finding out the artificially ripened fruits is difficult with human eye observation. To aid the detection we have developed a device which uses image processing to find the artificially ripened mangoes. The proposed device gets an input image of mango under test and compares the features (histogram values) with a naturally ripened one and detects fruits which are ripened artificially. This method makes usage of the Smartphone which runs android application that is installed in it and the image processing is executed to detect the artificially ripened fruits. The proposed system has an efficiency of 91% in the identification of the fruits ripened artificially.

The research aims to create a robust cold storage monitoring system for trucks, focusing on parameters like temperature, humidity, and harmful gases. Using nano power temperature, humidity, gas and LDR sensors, the system sets predefined thresholds for each parameter. The MS1089A features energy harvesting and a long battery life. The MS1089A has an I2C interface in addition to other time and power-saving features and it is accurate (±3 °C). By monitoring the temperature and safeguarding the surrounding environment, the nano power temperature sensor is ideal for environmental monitoring. When exceeded or fallen below, automatic notifications with GPS location are sent through Telegram to relevant authorities. Bidirectional communication via a Telegram bot allows users to remotely query sensor values. GPS technology enables live tracking for better cold storage unit management during transportation. The research is scalable, highlighting the potential of IoT in enhancing operational efficiency and reducing risks in cargo transportation. In summary, it integrates wireless sensors, an ESP32 microcontroller and Telegram messaging for a comprehensive cold storage monitoring solution, ensuring the safe transport of temperature-sensitive cargo.