ATMOSPHERIC
AIR QUALITY
SENSORS
Electrochemical cross-sensitivity correction, hygroscopic PM correction, solar MPPT, LoRaWAN mesh, and CEMS-compliant data acquisition — precision sensing built into every layer.
The Engineering Problem
Environmental Sensing Is a Measurement Science Problem, Not Just a Hardware Problem
Consumer-grade sensors ship with ±20% accuracy that collapses in the field. A 90% RH environment shifts a CO reading by hundreds of ppm without correction. Optical PM sensors calibrated on a single reference aerosol drift by factors — not percentages — near coastal fog or a wood-burning source.
Cross-sensitivity matrices, hygroscopic PM correction, pressure-altitude adjustment, and TDR soil moisture calibration are not post-processing steps — they run on the embedded processor sample by sample. The physics must be compensated in firmware, not corrected on a server.
We've deployed sensors across city-scale air quality networks, agricultural IoT platforms, and 40 CFR Part 75 CEMS-adjacent installations. Our firmware carries the calibration science — and our hardware is designed to stay calibrated in the field, not just at the factory.
Environmental Sensor Categories We Build
From indoor air quality monitors to CEMS stacks — precision sensing hardware across the full environmental monitoring spectrum.
Ambient Air Quality Monitors
Particulate Matter Sensors
Weather Stations & Micromet Systems
Soil & Agricultural Sensors
Water Quality & Hydrology
Indoor Air Quality Monitors
CEMS & Stack Monitoring
Radiation & Nuclear Sensors
Electrochemical Sensor AFE
Three-electrode cell biasing, transimpedance amplifier design with femtoampere noise floors, cross-sensitivity correction matrices, and temperature-compensated baseline tracking.
NDIR & Optical Gas Detection
Non-dispersive infrared source-detector design, bandpass filter selection, dual-beam reference compensation, and pressure/temperature correction algorithms for CO2/CH4/CO.
Optical Particle Counter Design
Laser diode optics, photodetector transimpedance stages, particle sizing histogramming in firmware, and hygroscopic correction curves derived from calibration data.
LoRaWAN & LPWAN Integration
LoRaWAN Class A/C node firmware, adaptive data rate, duty cycle management, NB-IoT and LTE-M fallback, and end-to-end AES-128 encryption.
Solar MPPT & Energy Harvesting
Solar panel MPPT controller design, LiFePO4 and supercapacitor charge management, ultra-low-power sleep/wake scheduling, and sub-100µA system standby current.
Environmental Compensation
Real-time humidity interference correction, pressure-altitude adjustment, temperature coefficient cancellation, and span drift alarms with automatic recalibration triggers.
Edge Data Processing
On-device 15-minute averaging, rolling statistics, threshold alarming, data buffering during comms outages, and compression for constrained bandwidth channels.
IP67 & Field Hardening
Conformal coating, sealed cable glands, anti-condensation heater circuits, UV-stable materials qualification, and NEMA 4X/IP67 enclosure gasket design.
Chipsets & Platforms
Sensors, Platforms & Standards
Tested silicon and proven stacks — no experimental platform dependencies.
Urban & Industrial Air Quality Networks
City-Scale AQI Monitoring
Urban monitoring demands electrochemical cells with real-time cross-sensitivity correction for the NO/NO2/O3/CO interferent cocktail of traffic corridors, and PM sensors with automated laser drift compensation. Our LoRaWAN nodes run three months per charge, coordinate across multi-gateway city networks with ADR, and buffer six hours locally during outages. OpenAQ, PurpleAir, and city SCADA integration is standard.
Precision Agriculture & Soil Sensing
Field-Deployed Agri-IoT
Accurate soil moisture requires site-specific calibration curves for soil type, clay content, and bulk density — not a generic capacitance reading. Our TDR/FDR nodes include on-device polynomial correction and integrate with John Deere Operations Center and Climate FieldView via solar-powered LoRa backhaul.
Continuous Emission Monitoring Systems
40 CFR Part 75 CEMS
CEMS installations require DAHS compliance with 40 CFR Part 75 Appendix A, automated calibration gas injection sequencing, and substitute data algorithms for missing data periods. We build the sensor interface electronics, signal conditioning, and embedded DAHS firmware supporting 4-20mA/RS-232/Modbus analyzer inputs and EPA ERT-format certified data export.
Why Engineering Teams Choose Ankh
Sensor Physics Expertise
We know the failure modes of every sensing modality — humidity poisoning of EC cells, photodegradation of UV fluorescence sensors, and acoustic reflection errors in ultrasonic anemometers. Our designs account for them.
Field-Calibrated, Not Bench-Calibrated
Every sensor system we ship includes a calibration workflow designed for field conditions, not just the factory. Span checks, zero baselines, and automated drift detection built into firmware.
Network-Scale Architecture
We've designed city-scale air quality networks — hundreds of nodes, mixed connectivity, multi-tenant data pipelines. The hardware and firmware are built for scale from the start.
Regulatory & EPA Familiarity
CEMS data acquisition handling requirements, 40 CFR Part 75 Appendix A performance specifications, and EPA equivalency method testing documentation — we know the compliance landscape.
25-Node City Air Quality Network
A municipal environmental agency needed accurate, low-maintenance air quality monitoring across 25 urban locations — NO2, O3, PM2.5, and CO2 — without the capital cost of reference-grade analyzers at every site.
Designed a LoRaWAN-connected sensor network with real-time electrochemical cross-sensitivity correction and on-device hygroscopic PM compensation. 25 nodes deployed across traffic corridors and residential zones, operating 18 months without a field calibration visit.
- ±4 ppb NO2 field accuracy vs. reference analyzer after 6 months
- 18 months continuous operation without manual calibration visit
- 99.1% data availability across all nodes
300-Node Vineyard Soil & Microclimate Network
A 1,200-acre vineyard needed granular soil moisture and microclimate data across hundreds of monitoring points to drive precision irrigation scheduling — with multi-year autonomous operation and no manual intervention.
Built a 300-node solar-powered LoRaWAN sensor platform with TDR soil moisture nodes, site-specific polynomial calibration curves, and 12 micromet weather stations feeding a cloud irrigation scheduling algorithm.
- 12% reduction in irrigation water use in first growing season
- ±1.2% VWC soil moisture accuracy across 3 soil types
- 5-year projected battery/solar life validated in 18-month field trial
Let's Measure What Matters.
Whether you're building a city air quality network, an agricultural IoT platform, or a CEMS-compliant industrial installation — we engineer the sensing hardware and firmware that stays accurate in the field.
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