Computer vision and sensing
AI + IoT crop surveillance
A crop-monitoring prototype connecting YOLOv11 computer vision with LoRaWAN sensing during an IIT Delhi-associated R&D internship.
The system connected image-based crop monitoring with low-power communication, forcing model behaviour, sensors and field conditions to be considered together.
How can a vision model and constrained IoT link operate as one field prototype rather than two disconnected demos?
My contribution
- Developed the AI + IoT prototype during a January–June 2025 R&D internship.
- Integrated YOLOv11-based crop monitoring with LoRaWAN communication.
- Iterated on the model/data pipeline after lighting changes caused a weed misclassification.
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Question
Join perception to a field system
Useful crop monitoring requires sensing, inference and constrained communication to work together.
Method, as a sequence of decisions
- 01
Capture field imagery and sensor context.
- 02
Run YOLOv11-based crop/anomaly detection.
- 03
Transmit relevant observations over LoRaWAN.
- 04
Inspect field failures and revise data/model assumptions.
What the record actually supports
R&D internship period
January–June 2025 in the recovered record.
Vision foundation
Used for crop segmentation/anomaly detection.
Field connectivity
Low-power communication integrated into the prototype.
Evidence: CVs and UCD statement of purpose. IIT Delhi A.I.C./Aapah host wording needs certificate reconciliation.
Choices and trade-offs
Why inspect field errors?
Lighting variation exposed a weed misclassification, illustrating why deployment conditions belong inside the research loop.
What has not been established
- Exact host/employer wording awaits the internship certificate.
- No field-scale accuracy or reliability benchmark is claimed.
- The prototype record does not establish production deployment.
What I would investigate next
- Q1How should the data pipeline represent lighting and seasonal drift?
- Q2Which decisions should run locally versus across the LoRaWAN link?
No public paper or repository is attached yet. The case study is intentionally limited to the evidence in the supplied record.
Peer notes / Crop surveillance
See a missed assumption?
Research suggestions, methodological critique and relevant collaboration ideas are particularly useful.