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Embedded Intelligence Architecture

ESP32-S3 TinyML Local Neural Processing.

Designed for local on-device inference with zero video streaming and complete volatile SRAM privacy.

240MHz Dual-Core Engine

Quantized TinyML models designed to run directly on internal hardware silicon.

Volatile SRAM Overwrite

Thermal frames exist in volatile SRAM for edge inference and are immediately purged.

Open Research Framework

Designed to connect raw telemetry streams to open research and home automation pipelines.

Signals

What is happening?

Interpretation

What could it mean?

Understanding

Why is it happening?

Connection

What does this tell us?

Care

What should we do?

Concept Preview · Nature Translation Engine™

From raw thermal biometrics to natural human speech.

An interactive demonstration of how NIH-01 is designed to translate invisible leaf micro-climates into clear plant voice interpretations.

How NTE™ Works: Vriksh Vani doesn't literally make plants speak in human words. It measures biological signals (thermal shifts, VPD, VOCs), uses AI to interpret biophysical stress, and presents that interpretation in natural language.
Simulated Sensor Telemetry
CONCEPT DEMO
Leaf Temp
23.4°C
Computed VPD
0.85 kPa
Relative Humidity
58%
VOC Resistance
185 kΩ
Sample Transpiration Index98/100 Illustrative
Optimal Transpiration Homeostasis94% Confidence
Profile: Calm & Warm Profile
Signals Observed:Leaf thermal delta -1.8°C · VPD 0.85 kPa · Humidity 58% · Baseline MOX 185 kΩ

"My leaves are slightly cooler than the room air and ambient humidity is steady. Transpiration is operating peacefully, though I may enjoy a gentle sip of room-temperature water later this afternoon."

Operating Architecture

NIOS™ — How Vriksh Vani Understands Living Systems.

Nature Intelligence Operating System (NIOS™) bridges non-invasive biophysics, edge AI inference, and natural human communication.

NIOS™ Conceptual Operating Model

The three foundational layers connecting plants and humans

01 · SENSING

Biophysical Capture

LWIR Leaf Thermography · BME688 MOX Sensing · Ambient VPD & Relative Humidity

02 · INTELLIGENCE

Local Edge TinyML

ESP32-S3 INT8 Quantization · Stomatal Behavior Classification · Confidence Scoring

03 · HUMAN CARE

NTE™ Voice Guidance

Natural Spoken Language · Explanatory Guidance · Empathy & Intuitive Plant Care

STAGE 01SIGNAL

Biological Signal Capture

FLIR thermal arrays measure leaf temperature fluctuations; BME688 gas sensor captures VOCs.

STAGE 02OBSERVATION

Biophysical Telemetry

Local SHT41 ambient sensors compute real-time Vapour Pressure Deficit (VPD) to monitor transpiration load.

STAGE 03INTERPRETATION

Edge TinyML Classification

On-device ESP32-S3 compute evaluates candidate physiological states such as stomatal behavior, hydration-related stress, and thermal stress.

STAGE 04UNDERSTANDING

NTE™ Neural Voice Concept

Translates biophysical states into natural human expressions across multiple language profiles.

STAGE 05CONNECTION

Empathy-Driven Awareness

Transforms plant care from guesswork into an intuitive bond between human and living nature.

STAGE 06CARE

Actionable Guidance

Translates measured signals into possible plant-care insights before physical wilting occurs.

FLIR Thermal Leaf vs Air Visualizer

ILLUSTRATIVE THERMAL MODEL

Simulated Educational Model — Not Live Experimental Telemetry

Leaf Surface (Modeled)22.4°CTranspiration Cooling
Ambient Air Temp: 25.8°CModeled ΔT: -3.4°C (Model)

Illustrative Physics Model: Transpiration can produce measurable leaf-surface cooling relative to surrounding conditions. The magnitude varies with species, relative humidity, VPD, and airflow. The values above demonstrate a theoretical thermal model rather than live experimental hardware readings.

NIH-01 System Architecture

Non-Invasive Sensor Fusion → TinyML INT8 Engine → NTE™ Speech

Architecture & Dataflow Concept
LAYER 1: SENSOR ARRAYFLIR Lepton 3.5160x120 LWIR (±0.05°C NETD)Sensirion SHT41RH ±1.8% · Temp ±0.2°CBosch BME688Quad-Gas VOC & PressureLight & Acoustic ProbeAmbient Lux & Mic ArrayLAYER 2: TinyML INFERENCE ENGINEESP32-S3 Dual-Core240 MHz · 512KB SRAM · 16MB FlashSensor Fusion MatrixMagnus VPD & Delta-T SolverNTE™ ClassifierQuantized INT8 Tensor Runtime16 Emotion States (<128ms)LAYER 3: OUTPUT & INTERFACE1.5W SpeakerNTE™ Spoken Voice EngineBLE 5.0 & Wi-Fi 4App & Smart Home SyncOpen Data SyncAnonymized Opt-In StreamCC BY 4.0 Academic License
Local On-Device TinyML Inference (Privacy First)
Target <128ms Total Sensor-to-Speech Flow
Optional Encrypted Telemetry Synchronization
Core Capabilities Vision

Engineered for absolute clarity, crafted for beauty.

Every planned component inside the NIH-01 hub concept is chosen to respect plant biology and human privacy.

Planned Sensor

FLIR Thermal Biometrics

Targeting FLIR Lepton 3.5 thermal array to read true leaf surface temperature non-invasively without physical contact.

Planned Sensor

Bosch BME688 MOX Sensing

Designing with BME688 sensor to measure VOCs and environmental gas signals.

AI Concept

NTE Spoken Voice Engine

Translating biophysical readings into calm voice interpretations across multiple languages on-device.

Design Target

TinyML Edge Compute

Local-first neural inference designed for low latency with optional encrypted telemetry synchronization.

Privacy Standard

100% Volatile SRAM Privacy

Thermal frame buffers exist strictly in volatile RAM. No visual images or audio are ever recorded or stored.

Roadmap Integration

Matter & Smart Home Vision

Designed to integrate with Home Assistant, Apple Home, Google Home, and Alexa via Thread and Wi-Fi mesh protocols.

Ongoing Research

Species Research Library

Building species-specific biophysical profiles for tropicals, succulents, and indoor house plants step by step.

Design Craft

Kiln-Fired Artisan Ceramic

Designed with slip-cast biophilic ceramic fired at high temperatures to blend into living spaces.

Early Research Cohort

Join the Nature Intelligence Journey.

Be among the first to receive research updates, prototype access, and contribute to our plant biophysics datasets.

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