Robert Jhon Aracena — AI Engineer
Buildingintelligenceforthefield.
Bridging agriculture and artificial intelligence through research-grade systems deployed where they matter.
I take AI from the lab to the soil — from model training, through edge optimization, to deployment in real agricultural conditions.
Diagnostic Accuracy
Field-validated with real farmers
Edge Inference
On $15 hardware, no internet needed
Farms Served
Across multiple pilot deployments
Selected Work
01
AgriSense
A retrieval-augmented assistant for tomato disease diagnosis (LLM + RAG + edge inference).
92%
Accuracy
<3s
Response
02
ESP32 Leaf Disease Scanner
Edge-deployed computer vision system for real-time leaf disease detection using ESP32-CAM.
Read the case study180ms
Inference Time
$15
Hardware Cost
03
ARMS
Agricultural Resource Management System
Full-stack web platform for farm resource tracking, crop planning, and yield prediction.
Read the case study150+
Farms Active
40%
Time Saved
84%
Prediction Accuracy
ARMS dashboard — resource tracking and yield prediction
My practice spans the full pipeline: from training neural networks in Python and PyTorch, to quantizing models for ESP32 microcontrollers, to building the web interfaces that make it all accessible. I work at every layer of the stack because real agricultural AI demands it.
Where AI meets agriculture
Research
AgriSense: Retrieval-Augmented LLM System for Tomato Disease Diagnosis
International Conference on Agricultural AI, 2025
Edge-Optimized Deep Learning for Real-Time Leaf Disease Detection on ESP32
IEEE IoT Journal, 2024
Precision Irrigation Using IoT Sensors and Machine Learning
Smart Agriculture Workshop, 2024
* Placeholder publications — replace with your actual research papers
Contact
Let'sbuildsomethingthatgrows.
I'm open to AI engineering roles, research collaborations, and consulting in agricultural technology. Reach out directly.
© 2026 Robert Jhon Aracena
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