ABSTRACT :

Agriculture is an essential source of sustenance. In India, this sector has tremendous opportunities of large-scale employment for villagers. A survey report illustrated the dependency of the Indian population on agriculture i.e. nearly 70%. Here, agriculture consist of the composition of several crops depending on the climatic nature. However, most of the Indian farmers are still unaware of technical knowledge such as what kind of crop suits their farmland. Numerous heterogeneous diseases affect the production of crops and result as a profitable loss. This paper illustrates the pest diseases specifically with their impact on the current production of the crop. In addition, it shows the survey reports based on several detection techniques of image detection. It is important to search and develop more techniques in order to identify the pest disease before it creates a serious loss in crop production. The current method for the reduction of pest disease is to spray pesticides. However, this process severely affects the health of humans directly or indirectly. The pest detection techniques at the early stages can provide less need for spraying pesticides. The image detection technique emerges as an effective measurement tool in order to fight the infestation. This technique offers better crop management with production as it delivers the maximum protection to crops. Such techniques also minimize human errors and efforts as providing the feature of automatic monitoring over large fields.

EXISTING SYSTEM :

The backbone of the Indian economy is agriculture as over 70% population depends on it for their occupation. The total Gross Domestic Product (GDP) includes 17% contributions from the agriculture sector [1]. Therefore, it becomes necessary to identify plant diseases in crops. The composition of Indian agriculture including several crops such as wheat, rice, paddy, sugarcane, vegetables, pulses, fruits, etc. Indian farmers also produce many non-food items like rubber, cotton, bamboo, tea, coffee, etc. The developments in such crops depending on the strength of roots as well as leaves [2]. There is a number of factors that develop different diseases in the roots and leaves of the plant that damaged crops and finally reduces crop production. Early identification of diseases in plants can avoid these enormous losses. Therefore, there is a requirement for accurate detection in order to save the economy and strengthen the agriculture sector of India [3]. Several kinds of diseases reduce the plant growth rate or even depriving their existence. Due to the lack of knowledge, farmers have difficulties to predict such diseases, especially at early stages. Plant disease detection includes several fields such as biomedical [4][5]. Biomedical consists the several processes out of which the image processing methods are the most suitable for the current scenario. It starts with capturing of plant leaves as data collection and then feature extraction. It is the most reliable and efficient method for disease detection. It is also the time-saving process. It precisely reduces the use of pesticides with human efforts. Scientists propose several ideas for yields measurement in agriculture by using the resources (available in the laboratory) for efficient leaf disease identification. This paper illustrated several techniques for plant disease detection suggested by different scientists/researchers.

PROPOSED SYSTEM :

Researchers could solve complex problems through image processing technology. It depicts the exponential growth of digital technology in the agricultural research field. Insect pest detection automation has a realistic opportunity as image analysis. Several works provide the extension of the implementation methods through an automated detection system for the estimation of pest densities in rice fields. Rice production increases (as both quality and quantity) by applying the right pests management and pest counting from the collected specimens through crop technicians. It becomes easy to develop a highly efficient monitoring system through an automated system. Cameras can easily monitor and detect rice infestation.

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10