Intelligent Pest Identification and Management Device

Project Title

Intelligent Pest Identification and Management Device

Project Area of Specialization Artificial IntelligenceProject Summary

Besides climatic changes and natural disasters, pests turn out to be very dangerous for crop productivity. A recent example is of "Tiddi Dal” in the Punjab and Sindh provinces which has resulted in large-scale crop damages. The farmers and government departments failed to take control measures against the epidemic. This can be because of insufficient timely information, and lack of advanced tools for detecting and alerting any pest attack.

A common practice to monitor pests is through visual clues by qualified pest management staff from the Government Agriculture department. This is not only expensive and labor intensive, but also lacks the ability to identify and react to outbreak in real-time.

The recent outbreak, therefore, accentuates the need for developing an intelligent pest and weather monitoring system that could notify the farmers about any pest occurrences in real-time and therefore help them provide the means for taking efficient, viable, and timely decisions.

The aim of this final year design project is to develop a cost-effective smart in-field pest surveillance station that could provide timely control warnings and information on pest invasions and infestations. This system will provide in-field diagnostics via an IoT-sensor (camera) connected to a cloud server and installed on a trap device in the field. Sticky pheromone chemicals will be used to trap the pests in the trap. Images of the trapped pests will be processed via learning-based computer vision models, and information about the detected/recognized pests (e.g., whether there are useful or dangerous pests) will be stored and sent to the farmer’s mobile phone automatically. A weather station will also be integrated into the main framework that would provide useful information to the farmers 24 hours a day. Weather plays important role in pest management.

Project Objectives

• To develop a platform for integrated pest management and to monitor crop field conditions such as weather, humidity, temperature, etc. that can be used by farmers for the optimization of inputs and treatments.
• To develop a machine learning algorithm that can detect and recognize insects with over 90% accuracy based on time- and geo-tagged visual images
• To develop a prototype of smart insect trap that is portable and can be run using green energy sources such as solar.

Project Implementation Method

The project will be implemented in the following stemps:

Step 1: Develop CAD model of the trap

Step 2: Select and program IoT tools and devices

Step 3: Select relevant agricultural sensors and pheromones

Step 4: Fabricate the trap

Step 5: Collect insect data from local farms

Step 6: Choose and implement a suitable machine-learning algorithm

Step 7: Train, test, and deploy the developed algorithm

Step 8: Develop the mobile app

Step 9: Develop the weather monitoring station

Step 10: Integrate the whole system

Benefits of the Project

The proposed smart trap offers a wide range of benefits, such as:

• Reduced efforts in continuous pest monitoring by eliminating the need for field trips and in addition reduced pest monitoring costs
• Availability of real-time pest information via mobile phone alerts thereby saving time in detecting pest occurrences
• Mobile alerts about imminent pest attacks or any upsurges in pest appearances in an area
• The proposed framework will allow the knowledge and valuable experience of farmers and agriculturists to be shared and utilized in better ways by combining it with modern technology for developing valuable data on pest problems
• Reduction in overall production costs due to the utilization of lesser amounts of pesticide and subsequent improvement in the economic condition of farmers
• Precise area-specific targeted spray application based on the pest data
• Daily pest counts reports and pest images via mobile phone
• Help plan better preventative measures and decisions as to whether pesticides need to be applied or not based on the trapped pests and weather data
• A gradual introduction of advanced farming technology in Pakistan’s agriculture sector

This technology will give farmers and government agricultural departments the ability to take appropriate and well-versed decisions pertaining to pest problems, by making vital information about the field easily available to them on time. The increase in crop productivity and reduction in wastage and unnecessary utilization of chemical inputs will help improve the economic condition of farmers.

Technical Details of Final Deliverable

- A portable smart trap device with insect pheromone and android application + website

- Green energy source (solar panel) will be used to power the device.

- High-resolution camera attached to Raspberry Pi will be used to do in-field visual image processing and analysis.  

- The trap will be connected to cloud where from it will be presented on GUI and a mobile app

Final Deliverable of the Project HW/SW integrated systemCore Industry AgricultureOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development GoalsRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	69500
Camera	Equipment	1	6000	6000
Raspberry pi	Equipment	1	14000	14000
Pests pheromones	Miscellaneous	3	2000	6000
Cloud server cpu	Equipment	1	25000	25000
3g modem	Equipment	1	3000	3000
led light etc.	Equipment	1	500	500
12000mAh 12 V battery	Equipment	1	5000	5000
IoT and Internet Connectivity	Equipment	1	10000	10000