Abstract:

Food safety and hygiene are among the key concerns in order to prevent the wastage of food.

However, for lack of technology and ignorance about the effects of humidity, temperature, exposure to light and alcohol content on foods, food safety is not maintained well enough in Kenya.

This has led to massive losses in many food stores resulting from food decay. Currently, majority of food stores and warehouses still rely on manual monitoring of the atmospheric factors related to food quality.

These conventional food inspection technologies are limited to weight, volume, color and aspect inspection and as a result do not provide a lot of information needed on quality of food.

The quality of the food needs to be monitored and it must be prevented from rotting and decaying by the atmospheric factors like temperature, humidity and dark.

This project is focused on such a food monitoring system which suggests systematic use of various sensors to perform quality monitoring and control of food materials.

More precisely, this system consists of gas, temperature, light and humidity sensors, which provide the essential information needed for evaluating the quality of the packed or stored product.

This information is transmitted wirelessly to a computer system providing an interface where the user can observe the evolution of the product quality over time using the Internet of Things technology.

Later, the environmental factors can be controlled like by refrigeration, vacuum storage and other appropriate control measures.

The food quality monitoring system has the following aims and objectives. The system aim states the main function of the whole system and the system objectives identifies the individual tasks that the parts of the system should achieve.

The proposed system should be able to:

• Read temperature and relative humidity in the food store.
• Sense the intensity of light in the food store.
• Detect the emission of ethanol type of gases.
• Collect data from all the sensors and pass to LCD for display.
• Monitor the sensor data visually online.