Design & Development of a High-Sensitivity Micro barometer Infrasound sensor

1. Executive Snapshot

Summary

The National Technical Research Organisation (NTRO) requires the design and development of a high-sensitivity atmospheric microbarometer infrasound sensor capable of measuring sub-audible pressure fluctuations in the 0.01 Hz to 20 Hz frequency band [PS]. Infrasound waves travel thousands of kilometers with minimal atmospheric attenuation, making them critical for detecting covert nuclear tests, distant industrial explosions, rocket launches, volcanic eruptions, and severe weather phenomena [KNOWN]. The proposed system addresses the full hardware lifecycle: a high-precision differential pressure transducer coupled to a mechanical long-period pressure equalization reservoir (backing cavity with a calibrated capillary flow leak) [RESEARCHED], a low-noise analog front-end (AFE) with active temperature compensation [RESEARCHED], a weather-resistant IP67 environmental enclosure [INFERENCE], and a porous-pipe wind-noise reduction spatial filter [RESEARCHED]. The sensor interfaces with an open-market, high-resolution (24-bit) digitizer and real-time waveform visualization software (e.g., Obspy / SeisComP / Python GUI) to demonstrate end-to-end signal detection, sensitivity estimation, and laboratory characterization [PS].

Metadata

Fundamental System Objective

To engineer a low-noise, highly stable hardware microbarometer and wind-noise mitigation interface that captures sub-pascal infrasonic waves from 0.01 Hz to 20 Hz and streams high-fidelity digital waveforms to real-time analysis software for strategic monitoring [INFERENCE].

2. Problem Deconstruction

The explicit problem statement provided by NTRO requires a functional prototype infrasound sensor covering 0.01 Hz to 20 Hz along with nine (9) mandatory hardware architectural components (a–i) and five (5) laboratory evaluation demonstrations (a–e) [PS].

Atomic Requirements & Technical Interpretations

3. Stakeholders & User Needs

4. Requirements Traceability

5. Constraints & Environment Realities

1. Physical Scale of Pressure: Ambient static pressure is $\sim 101,325\text{ Pa}$. Infrasound waves of interest are $\sim 0.001\text{ Pa}$ to $10\text{ Pa}$ ($100\text{ dB}$ to $120\text{ dB}$ lower) [KNOWN]. Without a mechanical differential reference, the sensor diaphragm will pin to the rail or destroy its dynamic range [RESEARCHED].
2. Flicker Noise ($1/f$ Noise): Electronics operating at $0.01\text{ Hz}$ ($T = 100\text{ s}$) are severely degraded by semiconductor flicker noise [KNOWN]. Standard operational amplifiers are unusable; chopper-stabilized or zero-drift precision amplifiers are mandatory [RESEARCHED].
3. Thermal Drift: A temperature change of $1^\circ\text{C}/\text{hour}$ inside an enclosed reference cavity causes gas expansion according to the ideal gas law ($\Delta P = P \cdot \frac{\Delta T}{T} \approx 350\text{ Pa}/^\circ\text{C}$) [KNOWN]. This thermal pressure shift overwhelms infrasound signals ($1\text{ mPa}$) by 6 orders of magnitude without thermal insulation and capillary leaks [RESEARCHED].
4. Wind Turbulence: Outdoor wind speeds above $2\text{ m/s}$ generate incoherent pressure fluctuations up to several pascals in the $0.1$–$5\text{ Hz}$ band [RESEARCHED]. Spatial acoustic filtering (WNRS) is physically mandatory for outdoor testing [RESEARCHED].
5. Power & Field Logistics: Field deployments require low power consumption ($<100\text{ mW}$ total sensor draw) to run continuously on small solar panels or batteries [RESEARCHED].

6. Research Questions

1. Transducer Selection: Which sensor topology (piezoresistive differential MEMS, variable capacitance diaphragm, or optical displacement) delivers $<2\text{ mPa RMS}$ self-noise at $0.01\text{ Hz}$ while remaining affordable for student prototyping? [ASSUMPTION]
2. Capillary Dimensioning: What combination of capillary leak tube diameter ($d$), length ($L$), and reference volume ($V_{\text{ref}}$) yields an exact mechanical cutoff frequency $f_c = 0.01\text{ Hz}$ ($\tau = R_{\text{acoustic}} \cdot C_{\text{acoustic}} \approx 15.9\text{ seconds}$)? [INFERENCE]
3. Calibration Traceability: How can a student team build an acoustic calibration chamber/pistonphone capable of generating stable $0.01\text{ Hz}$ pressure oscillations ($0.1\text{ Pa}$ to $1\text{ Pa}$) without certified NMI infrastructure? [NEEDS VALIDATION]
4. Digitizer Interface: Which open-market 24-bit audio/geophysical digitizer or high-precision ADC board (e.g., ADS1220 / ADS127L01 / Raspberry Shake digitizer) can be sourced reliably in India? [NEEDS VALIDATION]

7. Data Requirements & Sources

8. Existing Solutions & Gap Analysis

9. Candidate Solution Approaches

Approach 1: High-Precision Differential Piezoresistive MEMS Transducer with Pneumatic Capillary Filter & Chopper AFE (Recommended)

• Mechanism: Uses a high-sensitivity micromachined piezoresistive differential pressure transducer (e.g., AllSensors DLVR / Amphenol NPC-1210 / Honeywell TruStability series) [RESEARCHED]. Port A is exposed to atmospheric pressure via a WNRS. Port B is connected to a thermally insulated $0.5\text{ L}$ reference volume fitted with a glass micro-capillary tube (establishing $f_c = 0.01\text{ Hz}$) [RESEARCHED]. The output voltage is processed by a zero-drift chopper operational amplifier and 24-bit delta-sigma ADC [RESEARCHED].
• Complexity: Medium (Precision acoustic mechanics + low-noise analog PCB design).
• Cost: Low ($\sim ₹15,000$ to $₹25,000$ for prototype).
• Hackathon Feasibility: High (Components are commercially available; capillary sizing is physically verifiable).
• Production Feasibility: Very High (Scalable PCB manufacturing and 3D/CNC enclosure fabrication).

Approach 2: Sealed Dual-Capsule LVDT / Inductive Displacement Microbarometer

• Mechanism: Uses an evacuated metallic aneroid capsule (similar to classical CEA MB2000/MB3 designs) whose micro-deformations ($\sim\text{nm/Pa}$) are detected using a Linear Variable Differential Transformer (LVDT) or inductive sensor [RESEARCHED]. Static pressure compensation is achieved by electro-mechanical balance coils or long-period motor equalization [RESEARCHED].
• Complexity: Extremely High (Requires sub-micron mechanical machining, custom LVDT coil winding, and precision magnetic shielding).
• Cost: High ($>₹1,500,000$ for custom precision machining).
• Hackathon Feasibility: Very Low (Unrealistic to machine sub-micron capsule mechanisms within hackathon timelines).
• Production Feasibility: Medium (High cost per unit, specialized defense manufacturing required).

Approach 3: Fully Digital MEMS Micro-Barometer Array with Active DSP Software Equalization

• Mechanism: Employs multiple ultra-high-resolution digital barometers (e.g., Bosch BMP390 / ST LPS22HH) operating at high sampling rates, subtracting static DC barometric pressure in software/DSP using digital high-pass IIR filtering without a mechanical capillary [INFERENCE].
• Complexity: Low (Purely electronic & software).
• Cost: Very Low ($<₹5,000$).
• Hackathon Feasibility: High.
• Production Feasibility: Rejected for Primary Infrasound. Standard digital barometers have a self-noise floor of $\sim 1\text{ Pa RMS}$ at $0.01\text{ Hz}$, which is $1,000\times$ higher than the required $<2\text{ mPa}$ infrasound threshold [RESEARCHED]. They clip under strong ambient wind or saturate 24-bit ADC dynamic range when subtracting $100,000\text{ Pa}$ static pressure [INFERENCE].

10. Recommended Approach & Why

Selection

Approach 1 (Piezoresistive Differential MEMS with Pneumatic Capillary Filter & Chopper AFE) is selected [INFERENCE].

Justification & Rejections

1. Why Approach 3 was rejected: Purely digital surface barometers suffer from $1/f$ noise and quantization limits when measuring $1\text{ mPa}$ fluctuations on top of a $101,325\text{ Pa}$ baseline [KNOWN]. A mechanical differential reference port is physically indispensable to isolate acoustic pressure from barometric head pressure [RESEARCHED].
2. Why Approach 2 was rejected: Manufacturing aneroid diaphragm capsules with nm-scale displacement feedback requires specialized precision metrology facilities unavailable to student teams [INFERENCE].
3. Why Approach 1 wins: It matches state-of-the-art low-cost research microbarometers (such as the KNMI mini-MB and Infra-NMT) [RESEARCHED]. It delivers true differential pressure sensing down to $0.01\text{ Hz}$, uses accessible low-noise electronics, allows physical tuning of the capillary acoustic cutoff, and fits comfortably within a student team's build capabilities [INFERENCE].

11. Technical Architecture

[ Atmospheric Acoustic Input ]
               │
               ▼
┌────────────────────────────────────────────────────────────────────────┐
│ MECHANICAL / ACOUSTIC FRONT-END                                       │
│                                                                        │
│  Ambient Port ──► [ Porous Pipe Wind-Noise Reduction System (WNRS) ]   │
│                             │                                          │
│                             ├──────────────────────────────┐           │
│                             ▼                              ▼           │
│                   ┌──────────────────┐          ┌────────────────────┐ │
│                   │ Port A (Sensing) │          │ Capillary Flow Leak│ │
│                   └─────────┬────────┘          └─────────┬──────────┘ │
│                             │                             ▼            │
│                             │                   ┌────────────────────┐ │
│                             │                   │ Thermal Insulated  │ │
│                             │                   │ Reference Chamber  │ │
│                             │                   │ (500 mL Cavity)    │ │
│                             │                   └─────────┬──────────┘ │
│                             │                             ▼            │
│                             │                   ┌────────────────────┐ │
│                             │                   │ Port B (Reference) │ │
│                             │                   └─────────┬──────────┘ │
│                             │                             │            │
│                             ▼                             ▼            │
│                   ┌──────────────────────────────────────────┐         │
│                   │ Piezoresistive Differential Strain Cell  │         │
│                   └────────────────────┬─────────────────────┘         │
└────────────────────────────────────────┼───────────────────────────────┘
                                         │ Microvolt Differential Signal
                                         ▼
┌────────────────────────────────────────────────────────────────────────┐
│ LOW-NOISE ANALOG FRONT-END (AFE)                                       │
│                                                                        │
│  ┌─────────────────────────┐     ┌──────────────────────────────────┐  │
│  │ Precision Low-Drift     │ ──► │ Zero-Drift Chopper Instrument.   │  │
│  │ Voltage Reference (<5ppm│     │ Amplifier (ADA4522 / LTC2057)   │  │
│  └─────────────────────────┘     └────────────────┬─────────────────┘  │
│                                                   ▼                    │
│  ┌─────────────────────────┐     ┌──────────────────────────────────┐  │
│  │ Thermal Sensor (PT1000) │ ──► │ Active Low-Pass Anti-Aliasing    │  │
│  │ Signal Conditioning     │     │ Filter (Sallen-Key fc=25 Hz)     │  │
│  └─────────────────────────┘     └────────────────┬─────────────────┘  │
└────────────────────────────────────────┼───────────────────────────────┘
                                         │ Low-Noise Analog Volts
                                         ▼
┌────────────────────────────────────────────────────────────────────────┐
│ DATA ACQUISITION & DIGITIZER HARDWARE                                  │
│                                                                        │
│  ┌──────────────────────────────────────────────────────────────────┐  │
│  │ 24-Bit Delta-Sigma ADC (ADS1220 / ADS127L01 @ 100 SPS)           │  │
│  └────────────────────────────────┬─────────────────────────────────┘  │
│                                   │ SPI / UART                         │
│                                   ▼                                    │
│  ┌──────────────────────────────────────────────────────────────────┐  │
│  │ Microcontroller / SBC (ESP32-S3 / STM3238 / Raspberry Pi)        │  │
│  │ - Precision NTP/GPS Timestamping                                 │  │
│  │ - SeedLink Protocol / Serial Packetizer                          │  │
│  └────────────────────────────────┬─────────────────────────────────┘  │
└────────────────────────────────────────┼───────────────────────────────┘
                                         │ USB / Ethernet / Wi-Fi
                                         ▼
┌────────────────────────────────────────────────────────────────────────┐
│ OPEN MARKET WAVEFORM DISPLAY & ANALYSIS SOFTWARE                       │
│                                                                        │
│  ┌─────────────────────────┐     ┌──────────────────────────────────┐  │
│  │ Real-Time Waveform GUI  │     │ ObsPy / Python Signal Processing │  │
│  │ (PlotJuggler / SeisComP)│ ──► │ - Bandpass Filter (0.01 - 20 Hz) │  │
│  │ Stream Plotting         │     │ - PSD & Self-Noise Floor Curve   │  │
│  └─────────────────────────┘     │ - STA/LTA Infrasound Trigger     │  │
│                                  └──────────────────────────────────┘  │
└────────────────────────────────────────────────────────────────────────┘

Detailed Data-Flow Narrative

1. Acoustic Pressure Incident: Atmospheric pressure variations ($0.01\text{–}20\text{ Hz}$) enter the star-shaped Porous-Pipe Wind-Noise Reduction System (WNRS), averaging out localized wind turbulence [RESEARCHED].
2. Differential Mechanical Filtering: The averaged pressure wave directly hits Port A (the active sensing face of the differential transducer) [RESEARCHED]. Concurrently, the pressure wave passes through the calibrated glass micro-capillary flow leak into the $500\text{ mL}$ insulated reference cavity (Port B) [RESEARCHED].
   • For high-frequency fluctuations ($f > 0.01\text{ Hz}$), the capillary restriction prevents rapid air flow into the cavity; Port B remains at steady static pressure, creating a true differential pressure across the diaphragm ($\Delta P = P_{\text{acoustic}}$) [RESEARCHED].
   • For slow barometric shifts ($f < 0.01\text{ Hz}$), air bleeds through the capillary, equalizing pressure across both ports ($\Delta P \approx 0$), eliminating baseline saturation [RESEARCHED].
3. Transduction & Thermal Sensing: The piezoresistive bridge converts diaphragm deflection into a differential microvolt signal ($\sim 20\text{–}50\text{ }\mu\text{V/Pa}$) [RESEARCHED]. An integrated PT1000 RTD continuously monitors temperature inside the cavity [RESEARCHED].
4. Analog Front-End Processing: An ultra-low drift voltage reference ($<5\text{ ppm/}^\circ\text{C}$) excites the bridge [RESEARCHED]. A zero-drift chopper instrumentation amplifier (ADA4522/LTC2057) boosts the signal by $100\times$ with zero $1/f$ flicker noise [RESEARCHED]. A 4th-order active Sallen-Key low-pass filter cuts off signals above $25\text{ Hz}$ to prevent alias distortion [INFERENCE].
5. 24-Bit Digitization & Timestamping: The 24-bit Delta-Sigma ADC samples the signal at $100\text{ SPS}$ with an effective resolution $>20\text{ bits}$ [RESEARCHED]. The microcontroller tags each sample packet with precise UTC timestamps derived from an onboard GPS module or NTP clock [INFERENCE].
6. Streaming & Visualization: Data packets are transmitted via SeedLink over Serial/Ethernet to the open-market visualization software (ObsPy / PlotJuggler) for live waveform rendering, power spectral density calculation, and threshold-based event triggers [PS].

12. Technology Stack

13. AI/ML Justification

AI/ML Evaluation

• Is AI required for primary sensing? NO. Primary transduction, acoustic filtering, temperature compensation, signal conditioning, and digitizing MUST remain deterministic hardware and physics-based functions [INFERENCE].
• Is AI useful downstream? YES (Optional Software Layer). AI can be applied strictly in the post-processing software layer for automated event classification (e.g., distinguishing industrial blasts vs volcanic eruptions vs meteors) [RESEARCHED].

Downstream AI Module Analysis (Optional Software Feature)

1. Purpose: Classify detected infrasonic signals into event categories (Industrial Explosion, Thunder, Rocket Launch, Wind Noise Artifact) [INFERENCE].
2. Model Type: 1D-CNN or LightGBM on time-frequency spectrogram features (STFT / Continuous Wavelet Transform) [RESEARCHED].
3. Input: 10-second waveform segment ($1000\text{ samples}$ @ $100\text{ Hz}$) + spectrogram matrix [INFERENCE].
4. Output: Multi-class classification probability + confidence score [INFERENCE].
5. Data Required: Publicly available IRIS/CTBTO infrasound event waveform benchmarks [RESEARCHED].
6. Why AI is Preferable for Classification: Hand-crafted thresholds struggle with complex dispersion patterns of long-distance infrasound propagation [INFERENCE].
7. Evaluation: Classification Accuracy, F1-Score, and False Alarm Rate (FAR) [INFERENCE].
8. Failure Mode: Misclassification of a novel acoustic signal. System falls back to raw waveform display; no impact on hardware sensing integrity [INFERENCE].
9. Human Oversight: All AI event triggers require analyst review in the GUI [INFERENCE].

14. Data Architecture & Offline/Low-Network Design

┌────────────────────────────────────────────────────────────────────────┐
│ SENSOR EMBEDDED FIRMWARE                                               │
│                                                                        │
│   ┌──────────────────────┐      ┌───────────────────────────────────┐  │
│   │ 24-Bit ADC Samples   │ ───► │ Circular Ring Buffer in RAM       │  │
│   │ (100 Hz Raw Stream)  │      │ (30 Seconds Buffer)               │  │
│   └──────────────────────┘      └─────────────────┬─────────────────┘  │
│                                                   │                    │
│                                                   ▼                    │
│                                 ┌───────────────────────────────────┐  │
│                                 │ MicroSD Card Local Storage        │  │
│                                 │ (mini-SEED Binary File Format)    │  │
│                                 └─────────────────┬─────────────────┘  │
└───────────────────────────────────────────────────┼────────────────────┘
                                                    │ SPI / SDIO
                                                    ▼
┌────────────────────────────────────────────────────────────────────────┐
│ NETWORK TRANSMISSION & SYNCHRONIZATION                                 │
│                                                                        │
│                    ┌───────────────────────────────────┐               │
│                    │ Connection Status Detector        │               │
│                    └─────────────────┬─────────────────┘               │
│                                      │                                 │
│            ┌─────────────────────────┴────────────────────────┐        │
│            ▼                                                  ▼        │
│   [ ONLINE MODE ]                                    [ OFFLINE MODE ]  │
│   - Stream SeedLink TCP Packets to Server            - Log locally     │
│   - Sync NTP Time Server                             - Retain SD files │
│   - Real-time Plotting                               - Auto-backfill   │
└────────────────────────────────────────────────────────────────────────┘

Key Data Architecture Specifications

• Local Storage & Format: MicroSD card logging using the international geophysical standard mini-SEED format (highly compressed binary format optimized for time-series data) [RESEARCHED].
• Caching & Conflict Handling: Internal $32\text{ MB}$ RAM ring buffer prevents data loss during MicroSD write cycles [INFERENCE]. Upon network reconnection, a SeedLink backfill protocol automatically transmits missing historical data packets without duplicating entries [RESEARCHED].
• Bandwidth Reduction: Raw 24-bit data @ 100 SPS generates only $\sim 34.5\text{ MB/day/sensor}$, making it suitable for low-bandwidth cellular (2G/4G) or satellite telemetry links [INFERENCE].

15. Security, Privacy & Governance

• Data Sensitivity: Infrasound waveforms recorded near sensitive industrial or military facilities carry strategic national security value [INFERENCE]. Raw telemetry stream must be encrypted using AES-256 before cellular/satellite transmission [INFERENCE].
• Authentication & Access Control: Microcontroller management interface protected by Mutual TLS (mTLS) certificate authentication [INFERENCE]. Software dashboard enforces Role-Based Access Control (RBAC) [INFERENCE].
• Data Ownership & Governance: All prototype outputs, designs, and recorded waveforms remain the exclusive intellectual property of NTRO and the sponsoring ministry [PS].
• Regulatory & Validation Disclaimer: The prototype produced during the SIH hackathon is a proof-of-concept hardware system. Field operational deployment requires independent metrological validation by accredited laboratories (e.g., NPL India or CSIR-NGRI) [INFERENCE].

16. MVP Scope (Hackathon Build)

┌─────────────────────────────────────────────────────────────────────────┐
│ HACKATHON MVP SCOPE (MUST BUILD)                                        │
│                                                                         │
│  [1] Physical Sensor Prototype                                          │
│      - Piezoresistive differential pressure cell with capillary leak    │
│      - Thermally insulated reference chamber                            │
│      - Low-noise AFE PCB with chopper op-amp & 24-bit ADC               │
│                                                                         │
│  [2] Wind-Noise Reduction Interface (WNRS)                              │
│      - Miniaturized 4-port porous tube spatial filter                   │
│                                                                         │
│  [3] Data Acquisition & Interface                                       │
│      - Microcontroller running 100 Hz sampler firmware                  │
│      - USB/Serial data streaming protocol                               │
│                                                                         │
│  [4] Open Software Display & Analysis GUI                               │
│      - Real-time waveform display (ObsPy / Python GUI)                  │
│      - Bandpass filter (0.01 Hz - 20 Hz)                                │
│      - Power Spectral Density (PSD) plot & Noise Floor Calculation      │
└─────────────────────────────────────────────────────────────────────────┘
                                     │
                                     │ OUT OF SCOPE FOR HACKATHON
                                     ▼
┌─────────────────────────────────────────────────────────────────────────┐
│ PRODUCTION / FUTURE EXTENSIONS                                          │
│                                                                         │
│  - Multi-station array beamforming & direction-of-arrival (DOA)         │
│  - Hermetically sealed titanium housing with MIL-SPEC connectors        │
│  - Satellite / Iridium direct uplink hardware                           │
│  - ISO/IEC 17025 accredited NPL calibration certificate                 │
└─────────────────────────────────────────────────────────────────────────┘

17. Live Demo Simulation Plan

Demonstrating ultra-low frequency infrasound ($0.01\text{ Hz}$) live inside a hackathon hall is challenging due to ambient noise and lack of large pressure chambers. The team will execute a 3-Tier Simulated / Physical Demonstration:

┌────────────────────────────────────────────────────────────────────────┐
│ LIVE HACKATHON DEMO STRATEGY                                           │
│                                                                        │
│  TIER 1: Physical Infrasound Signal Generation (In-Person Hardware)    │
│  - Mechanical Syringe / Sealed Accordion Bellows Test rig:             │
│    Slow manual/motorized compression creates 0.1 Hz - 1 Hz pressure    │
│    pulses (~1 - 5 Pa) inside a sealed 2L acrylic test box.             │
│  - Real-time sensor response visible on GUI instantly.                 │
│                                                                        │
│  TIER 2: Self-Noise Floor & Baseline Stability Test                    │
│  - Cap the sensor ports in an insulated chamber.                       │
│  - Live compute PSD (Power Spectral Density) showing sub-mPa self-noise│
│    floor across 0.01 Hz to 20 Hz.                                      │
│                                                                        │
│  TIER 3: Open-Market Software & Reference Injection                    │
│  - Inject historical public infrasound event (e.g., Tonga eruption /   │
│    rocket launch) into open-market digitizer pipeline to demonstrate   │
│    waveform display, filtering, and event detection capability.        │
└────────────────────────────────────────────────────────────────────────┘

18. Implementation Roadmap

Target Deadline: 30 September 2026 [PS].

┌────────────────────────────────────────────────────────────────────────┐
│ IMPLEMENTATION ROADMAP (Sized to 30 September 2026)                    │
│                                                                        │
│ PHASE 1: Acoustic Physics & Circuit Design [Oct 2025 - Dec 2025]       │
│ ├─ Capillary leak dimensioning & reference cavity CAD modeling         │
│ └─ Schematics & PCB layout for Chopper AFE & 24-bit ADC                │
│                                                                        │
│ PHASE 2: Hardware Prototyping & Mechanical Assembly [Jan 2026 - Mar 2026]│
│ ├─ Fabrication of reference chamber & CNC/3D printed enclosure         │
│ ├─ PCB assembly, soldering, and low-noise shielding                    │
│ └─ Microcontroller firmware (100 Hz sampling & mini-SEED logging)      │
│                                                                        │
│ PHASE 3: Software Integration & Bench Calibration [Apr 2026 - Jun 2026]│
│ ├─ ObsPy Python real-time GUI & SeedLink receiver development          │
│ ├─ Syringe/bellows low-frequency pressure pulse testing                │
│ └─ Frequency response & self-noise floor estimation                    │
│                                                                        │
│ PHASE 4: Outdoor Field Testing & WNRS Validation [Jul 2026 - Aug 2026] │
│ ├─ Deployment with 4-arm porous pipe WNRS array in outdoor environment │
│ └─ Temperature drift verification across outdoor day/night cycle       │
│                                                                        │
│ PHASE 5: Hardening, Documentation & Final Presentation [Sep 2026]      │
│ └─ Final system dossier, video demonstration, and SIH submission       │
└────────────────────────────────────────────────────────────────────────┘

19. Testing & Validation Plan

20. Risk Register

21. Cost & Scalability

Hackathon Prototype Build Cost

Commercial Production Cost (Per Unit at 100+ Scale)

• Estimated Hardware Cost: ₹8,500 per complete sensor unit [INFERENCE].
• Deployment Economics: Commercial microbarometers cost over ₹5,000,000 ($>$6,000$ USD). An indigenous low-cost sensor enables dense monitoring networks across borders, active volcanoes, and industrial zones at a fraction of international procurement costs [INFERENCE].

22. Differentiation

23. Future Scope

1. Multi-Element Infrasound Array Integration: Link 3 to 4 microbarometers in a $100\text{ m}$ spatial array to perform Progressive Multi-Channel Correlation (PMCC) beamforming for real-time azimuth and wave velocity estimation [RESEARCHED].
2. MEMS Vacuum-Sealed Diaphragm Integration: Transition from capillary differential reference cavities to micro-fabricated vacuum reference cavities for enhanced long-term drift stability [RESEARCHED].
3. Satellite IoT Telemetry: Add direct Satellite/Iridium data transceivers for autonomous deployment in remote Himalayan border regions [INFERENCE].

24. Assumptions & Open Items Log

Consolidated Assumptions

• [ASSUMPTION] Commercial differential MEMS pressure sensors (e.g., Amphenol NPC-1210 / AllSensors DLVR) can be procured by student teams within India in under 3 weeks.
• [ASSUMPTION] A $0.5\text{ L}$ sealed acrylic/aluminum reference cavity combined with a $0.2\text{ mm}$ glass capillary tube provides a stable mechanical high-pass corner frequency near $0.01\text{ Hz}$.
• [ASSUMPTION] A motorized syringe or bellows assembly in a sealed container provides a sufficient low-frequency physical pressure signal for live hackathon jury demonstrations.

Consolidated Open Items & Validation Actions

• [NEEDS VALIDATION] Verify the exact noise floor parameters specified in the NTRO PS attached table (Google Drive file) against the standard CTBTO Low Noise Model.
• [NEEDS VALIDATION] Determine whether the evaluation committee requires RS-232, Ethernet, or USB physical interfaces for open-market digitizer integration.
• [NEEDS VALIDATION] Test whether local agricultural porous soaker hose materials provide adequate spatial averaging impedance comparable to certified CTBTO WNRS porous pipes.

Final Recommendation

Proceed with the development of Approach 1 (Piezoresistive Differential MEMS with Pneumatic Capillary Filter & Chopper AFE). It directly satisfies every requirement of SIH26144, achieves physical differential sensing down to $0.01\text{ Hz}$, and avoids the severe $1/f$ noise and dynamic range saturation flaws of generic digital barometer approaches [INFERENCE].

Recommended Stack

• Hardware Sensing: Amphenol NPC-1210 / AllSensors DLVR Differential MEMS Transducer
• Analog Front-End: ADA4522 Zero-Drift Chopper Op-Amp + Active Sallen-Key Low-Pass Filter
• Digitizer: ADS1220 24-Bit Delta-Sigma ADC + ESP32-S3 Microcontroller
• Wind-Noise Interface: 4-Arm Porous Hose Spatial Array
• Software: Python ObsPy + PlotJuggler + SeedLink Protocol

Biggest Dependency

Sourcing high-sensitivity, low-range differential pressure transducers ($\pm 125\text{ Pa}$ or $\pm 250\text{ Pa}$ full scale) with exposed dual differential ports [INFERENCE].

Biggest Risk

Flicker noise ($1/f$) and thermal drift overwhelming the low-frequency ($0.01\text{ Hz}$) pressure signal [RESEARCHED].

Biggest Technical Challenge

Accurately calibrating the acoustic micro-capillary leak to achieve an exact $0.01\text{ Hz}$ ($T = 100\text{ s}$) mechanical cutoff frequency without a metrological pressure chamber [RESEARCHED].

First 5 Actions

1. Procure Transducer: Order differential MEMS pressure sensors (Amphenol NPC-1210 / AllSensors DLVR) and ADA4522 chopper op-amps [INFERENCE].
2. Calculate Capillary Geometry: Run fluid dynamics formulas ($\tau = R_a \cdot C_a$) to size the micro-capillary tube length and diameter for a $0.5\text{ L}$ reference cavity [RESEARCHED].
3. Simulate AFE Circuit: Model the low-noise amplifier and active anti-aliasing filter in LTspice to verify phase and gain response from $0.01\text{ Hz}$ to $20\text{ Hz}$ [INFERENCE].
4. Build Bench Test Chamber: Construct a sealed $2\text{ L}$ acrylic chamber with a motorized syringe pump to generate controllable $0.01\text{ Hz}$ to $5\text{ Hz}$ pressure pulses [INFERENCE].
5. Develop ObsPy Receiver: Write the Python SeedLink receiver script to stream and display live waveforms and compute Power Spectral Density (PSD) [RESEARCHED].

Validation Before Coding

• Verify that the chosen ADC achieves an Effective Number of Bits (ENOB) $>18\text{ bits}$ at $100\text{ SPS}$ to resolve sub-mPa pressure signals [RESEARCHED].
• Confirm that the capillary tube leak prevents static DC barometric shifts (e.g., door opening/closing) from saturating the AFE [INFERENCE].

Buildability Score /100

85 / 100 Reasoning: Highly feasible for a multi-disciplinary student team combining electronics, mechanical/fluid mechanics, and Python software skills. The hardware components are standard, though low-noise AFE layout and pneumatic capillary tuning require careful engineering [INFERENCE].

Confidence

HIGH (Supported by established academic literature on piezoresistive microbarometers from KNMI, Infra-NMT, and CTBTO IMS standards) [RESEARCHED].

Research Sources

1. Title: Implementation, Characterization, and Evaluation of an Inexpensive Low-Power Low-Noise Infrasound Sensor Based on a Micromachined Differential Pressure Transducer and a Mechanical Filter

   • URL: https://journals.ametsoc.org/view/journals/atot/29/9/jtech-d-11-00101_1.xml
   • Source Type: Academic Publication (Journal of Atmospheric and Oceanic Technology)
   • Supported Claim: Validates the feasibility of using commercial piezoresistive differential MEMS pressure sensors with capillary mechanical high-pass filters for low-noise infrasound ($0.01\text{–}20\text{ Hz}$).
   • Reliability: High

2. Title: The INFRA-EAR: a low-cost mobile multidisciplinary measurement platform for monitoring geophysical parameters

   • URL: https://amt.copernicus.org/articles/14/3301/2021/
   • Source Type: Peer-Reviewed Journal (Atmospheric Measurement Techniques, Copernicus)
   • Supported Claim: Demonstrates KNMI mini-microbarometer architecture using All Sensors DLVR MEMS differential sensor for broadband infrasound detection.
   • Reliability: High

3. Title: Infrasound sensors and their calibration at low frequency

   • URL: https://www.acoustics.asn.au/conference_proceedings/INTERNOISE2014/papers/p153.pdf
   • Source Type: Conference Proceedings (INTER-NOISE / Australian Acoustical Society)
   • Supported Claim: Documents CEA MB3 / MB2005 CTBTO microbarometer specifications, sensitivity ($20\text{ mV/Pa}$), resolution ($1.5\text{ mPa}$), and low-frequency calibration methods.
   • Reliability: High

4. Title: Chaparral 64S Infrasound Sensor Type Approval Evaluation Report

   • URL: https://chaparralphysics.com/sandiareport-64s.pdf
   • Source Type: Technical Report (Sandia National Laboratories / Chaparral Physics)
   • Supported Claim: Outlines test protocols for frequency response ($0.01\text{–}20\text{ Hz}$), self-noise measurements, and temperature sensitivity evaluation for microbarometers.
   • Reliability: High