Harshini Suresha

Synergistic AI Architectures and Bioengineered Systems for Agricultural Pest Detection and Control

AI & ML in Agriculture & Bioengineering

Year2024
LocationPES University
TagsCNN, ViT, DETR, Edge AI

A review of 150+ sources on CNN, ViT and DETR-based pest detection, ensemble classifiers, bioengineered pest control and edge-AI sensor fusion for precision agriculture.

Oct 2024 – Dec 2024 at PES University, supervised by Dr. Dinesh M S.

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Figure for Synergistic AI Architectures and Bioengineered Systems for Agricultural Pest Detection and Control
Methods
  1. 01
    Literature review

    Reviewed 150+ sources on AI-driven pest detection.

    Systematic review
  2. 02
    Vision models

    Compared CNNs, vision transformers, DETR-style object detection and handcrafted descriptors.

    EfficientNet, ResNet, Inception, ViT, DETR, SIFT, HOG
  3. 03
    Classical ML

    Random Forest, SVM, gradient boosting and ensembles for pest classification.

    Random Forest, SVM, XGBoost, LightGBM, CatBoost
  4. 04
    Bioengineered control

    Logic gates, neuromorphic circuits, biosensors and 3D bioprinting for biomimetic traps aimed at precise, low-impact control.

    Logic gates, Biosensors, 3D bioprinting
  5. 05
    Edge deployment

    On-device inference, sensor fusion, latency and low-power design for real-time monitoring in the field.

    Edge AI, Sensor fusion
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