Vaiga Agrihack 2023

Team Members

Rhithuja Suresh
Afwan Sha J
Vishnu Suresh Perumbavoor (VSP)
Akhiyaar Muhammed
Shinas Shanavas

THis is Vaiga Agrihack winning project

Read more here https://twitter.com/vspeeeeee/status/1639454744493080578?t=Z8leUs0BCQMJ1ZqP94ji4g&s=19

Project that won us Vaiga AgriHack 2023 & startup idea presentation at Palakkad.

Technologies used

• LoRa sensor (IOT device that use LoRa for communication)
• LoRa (physical layer technology for long range low power communication)
• LoRaWAN (networking protocol)

Sensors to predict BPH

• NPK Sensor (to detect nitrogen, phosphorus & potassium content in the soil)
• DTH11 sensor (Digital Temperature & Humidity sensor)
• Moisture sensor

Sensors to detect BPH

• Passive InfraRed radiation sensor
• TCS3200 color recognition sensor

Microcontroller

ATmega328 (created by Atmel in megaAVR family with modified harvard architecture & 8 bit RISC processor core)

Machine Learning algorithms

This projects eXtreme Gradient Boosting (XGB) algorithm for prediction and detection
XGB showed the highest accuracy of 99% in regression modeling

Input data

  1. Prediction
    • Nitrogen
    • Phosphorus
    • Potassium (NPK Sensors)
    • Humidity
    • Temperature (Digital Temperature & Humidity Sensors)
    • Moisture (Moisture sensor)

  2. Detection
    • Infrared radiation value (Passive InfraRed sensor)
    • hacadecimal value of paddy color (TCS3200)

(BPH generate a certain infrared radiation wavelength & changes paddy color to orange)

Tech stack

• Scikit-learn (ML library for prediction modling)
• eXtreme Gradient Boosting (ML regression algorithm)
• Stremlit (frontend)
• Pywhatkit (automated whatsapp message to farmers)
• Pandas (python library to work with spreadsheet)
• AWS (Cloud)