Fruit Disease and Freshness Identification By Image Processing Method Using Raspberry Pi

This article discusses a system that uses Raspberry PI to detect and prevent the spread of fruit illnesses. The k-avg cluster algorithm is used to analyse various images. It has several advantages for use in large agricultural farms and detects disease symptoms on fruit leaves immediately. The automatic detection of disease symptoms using image processing and the k-means cluster method is useful for tracking crops in the field of fungus and is thus an important research topic in fruit pharmaceutical research. The term “disease” refers to the type of fruit toxicity. This study presents the most effective method for identifying fruit diseases using image processing and alerting the system owner about the disease's cause by displaying the disease's name on the system owner's monitor display. Automatic disease symptom identification can help farmers improve their crops. These technologies, which are entirely automatic in their design and implementation, will be extremely useful in chemical applications. It will reduce the cost of pesticides and other goods. This will result in increased agricultural productivity.