Deploying embedded intelligence where it matters most — understanding and protecting ecosystems.

🧭 Mission

Most conservation monitoring today relies on human observers (expensive, limited scale) or satellites (delayed, low resolution). I’m building autonomous systems that bridge this gap — intelligent platforms for continuous, real-time ecological observation, powered by embedded AI.

Every subsystem I build — from CPU-based transformers to flight controllers — feeds this mission. Each prototype is a stepping stone toward field-deployable conservation systems.

🧩 Approach

Vertical integration from silicon to software: Embedded sensors → Edge compute → Training infrastructure → Deployment platforms. I build the full stack, one layer at a time.

🌿 Ecological Monitoring & Biodiversity Conservation The mission. TDR and EM soil probes, biodiversity sensors, and real-time environmental monitoring. Complete pipeline from senaors → edge storage and inference → cloud dashboards. Hardware design, sensor networks, and data federation for conservation deployments.

🚁 Autonomous Aerial Platforms Real-time INS, quaternion mathematics, Kalman filtering, and control systems (PID/LQR/MPC) for autonomous flight. Enables continuous aerial monitoring at scale.

⚡ Embedded AI Inference Proving transformers can run on CPU without GPU clusters or framework dependencies. Hand-optimized kernels in pure C with cache-aware layouts, vectorized operations and more. Enables on-device inference and pattern recognition in the field.

☁️ Antsand Platform: Sensors → Dashboards Antsand is my proprietary SaaS platform with a custom DSL for rapid UI generation—from blogs to mission-critical field command centers. Templated dashboards, federated deployment, and real-time data orchestration. Connects remote sensor networks to conservation decision-makers.

Full-Stack Flight Controller (WIP) — attitudeMathLibrary • stateEstimation • dynamic_models • controlSystems • inertial_navigation_system • AeroDynControlRig (OpenGL+ImGui simulator)

Embedded Systems — BLEDroneCode (NRF53 drone: Zephyr RTOS, sensor drivers, PWM motor control) • HandheldController (wireless integration with drone controller)

Hardware Test Rigs — ThrustStand (propulsion characterization) • DroneTestRig (multi-axis dynamic testing)

HPC AI — C-Transformer (pure C inference + backprop on Xeons x86, starting with GPT-2, expanding to other architectures)

I prefer depth over hype. Gaps in my knowledge make me uneasy, which forces me to strip away abstractions and understand mechanics from first principles. I'm comfortable reading datasheets, solving problems from source truth, and moving seamlessly across the stack from low-level C/HPC to JavaScript/HTML/CSS. I use 3D printing to rapidly move from idea to prototype.

I run Linux/AwesomeWM and prefer NXP, TI, and Nordic MCUs. Datasheet fluency means I'm not limited to Arduino/ESP32/Raspberry Pi just because they're popular—I can evaluate compute requirements and pick the right chip. My repositories reflect this: lots of C code, AI augmentation, and first-principles approaches.

A quick lab tour: One of my hidden talents is optimizing space. The illustration above shows my closet lab—4×7 ft containing 3-4 monitors, dual laptops (Windows + Linux), 3D printer, Akro-Mils storage for electronics, microscope, soldering station, oscilloscope, signal generator, and a multi-angle YouTube capture setup. I use vertical shelving to maximize surface volume. I also love woodworking, so my miter saw and tools live on a pegboard in the same space.

Revised periodically based on budget, resources, time, skill development, and life obligations.

I work in systematic cycles—building capability, validating in field, then expanding. Each stage builds on the previous, accelerating toward deployed conservation systems.

Stage 0 (2025-2026) — Foundation Hardening Flight controller software maturation • Antsand platform modernization • Core libraries production-ready • Documentation and visualization tools

Stage 1 (2025-2027) — First Deployment TDR sensor monitoring in bogs • Field command center prototype • Antsand integration for sensor data → dashboards • Ground truth collection • Power and connectivity validation

Stage 2 (2026-2028) — Autonomous Deployment Drone-based sensor placement in remote areas • Autonomous waypoint navigation • Payload release mechanisms • Extended range operations • Multi-site coordination

Stage 3 (2027-2029) — Embedded Intelligence Custom AI models for pattern recognition • C-Transformer deployment for species identification • Automated flight planning from sensor triggers • Multi-variable analysis (moisture + temperature + visual)

Stage 4 (2027-2031) — Sensor Expansion EM signature sensors for soil conductivity • Optical/multispectral imaging • Acoustic monitoring for biodiversity • Integrated multi-modal sensing • Cross-validation pipelines

Stage 5 (2028-2032) — Satellite Integration Satellite imagery integration with ground truth • Change detection algorithms • Large-scale monitoring (100+ hectares) • Antsand as unified interface (ground + aerial + satellite)

Stage 6 (Ongoing) — Scale & Repeat Deploy proven systems to new sites • Partner with conservation organizations • Expand sensor types as needed • Continuous refinement based on field data

I believe my chances of completing all of this are 0%. But who cares - no harm trying.

ANTSHIV ROBOTICS is currently a solo operation. I use AI augmentation to accelerate development while maintaining deep technical understanding across the stack.

Open to:

• Contract work on hard embedded/AI problems (especially conservation-adjacent)
• Collaborations with shared philosophy (understand first, abstract when necessary)
• Field deployments in challenging environments (remote, power-constrained, long-term autonomy)
• Conservation partnerships where embedded intelligence can make a measurable impact

Best fit for projects requiring:

• Understanding system constraints before choosing abstractions
• Power/compute-constrained environments
• Long-term deployment without framework dependencies

• 🎥 YouTube: Flight controller deep-dives, sensor builds, and embedded AI walkthroughs → @Antshiv Robotics
• 💬 Discord: Real-time discussions on C optimization, drone dynamics, and hardware choices → Join here
• 🌐 Antsand Platform: antsand.com