Smart Agriculture system project is based on various sensors, Internet of Things (IoT), Image Processing and Artificial Intelligence (AI) as follows - IoT based Monitoring of agricuture system using various sensors including smart camera, soil sensors, temperature sensors, barometer
Monitoring & Controlling of Smart Agriculture System using IoT with AI-based Disease Detection & Production Forecasting
Smart Agriculture system project is based on various sensors, Internet of Things (IoT), Image Processing and Artificial Intelligence (AI) as follows
- IoT based Monitoring of agricuture system using various sensors including smart camera, soil sensors, temperature sensors, barometer etc.
- It also controls motor which is used to supply the water from irrigantion system whenever required
- By using smart camera and image procesing, crops diseases are Detected & Yield will Forecasted
For the pest and disease control, IoT method would be applied. To detect the disease and pest on the land, it will be very useful if the detection system can be equipped with a smart phone. Modern techniques makes this possible. A farmer will be able to classify the types of diseases on the cotton plant by using the smart phone application. IoT technologies enable remotely monitoring of the environment information from the farm. Temperature, humidity, atmosphere pressure, water level, sunlight levels are monitored and sent to the cloud. Farmers can monitor the environment information of the farm from home. By analysing those data on machine learning model, we are trying to predict the possibilities of disease and pest infection. AI will be used to check health quality of crops through image processing and production of crops will be forecasted.
The people are relaying on agriculture to cope up with their essential needs. They cultivate and eat crops for this purpos, however crops production depends heavily on manual and labour work which is less efficient, time-consuming and expensive. Detection of crops diseases and pest need experience and experts. I would like to equip the young generation of in experience farmers with the IoT and AI system that can help in their farms. Therefore the research objectives of this FYP are
Followng is the prosed flow chart of project implemneation
Through image processing of crops disease and plant classification, we have tested don the photos of each types from the Internet. As we couldn't get the real sample of disease infected crops at this time, we couldn't test on real data set. The smart phone application shows three possible predictions on the screen. For most possible types of disease of pest.
1. Hardware
2. Software
3. Algorithms
Farmers are suffering from low productivity and low quality of crops. The root causes of this problem are lack of knowledge in farming, natural disasters, water supply problems, disease and pest. Those low productivity leads to lowering down the farmer income and losing the opportunity for international market. Farmer generally don't know the modern farming practices. So, for the lack of knowledge in farming the agronomistic from ministry of agriculture, non government organisations and regional governments are now working hard to disseminate the useful information for farming to farmers.
Following are the the few Potential Benefits of This Smart Agriculture System
1- Effective and Remotely Monitoring through Smart sensors instead of Traiditional Manual Techniques
2- Efficient and Remotely Controlling of Motors for Water Supply to avoid delay or wastage of water
3- Crops Production will be inceased significantly sue to favroable and fast response on requirments
4- Detection of disease through Image Processaing and samrt cameras is useful to take necessary actions in time
5- On the basis of crops heath and diseases effected, future yeild will be foracsted for good planning in advance
6- Good and Health crops will yield more production subsequently more and more revenue
This is the Proposed Design of FYP delierable

We have discuss to perform monitoring crops ( camera, soil, temperature & berometer sensors)
Controlling ( On/Off , camera control)
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Solar plates | Equipment | 1 | 10000 | 10000 |
| Battery | Equipment | 1 | 10000 | 10000 |
| Resberipi | Equipment | 1 | 15000 | 15000 |
| Audrina | Equipment | 1 | 1500 | 1500 |
| Camera | Equipment | 1 | 20000 | 20000 |
| Soil sensor | Equipment | 1 | 120 | 120 |
| Berometer sensor | Equipment | 1 | 150 | 150 |
| Level sensor | Equipment | 1 | 200 | 200 |
| Temperature sensor | Equipment | 1 | 120 | 120 |
| Motor | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 67090 |
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