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Practical Over Theoretical
We build working instruments, not position papers. Herald DSMO embodies our commitment to tangible scientific progress.
FAESR believes artificial intelligence should create abundance, not scarcity. We prove this through practical tools that advance human knowledge while remaining accessible to researchers, educators, and citizen scientists worldwide.
We build working instruments, not position papers. Herald DSMO embodies our commitment to tangible scientific progress.
Open-source software, published methodologies, community governance. Every algorithm is auditable, every process documented.
You own your observations. Choose Sovereign mode for complete local control, or Federated mode to contribute to open science—your data, your choice.
Technology should multiply opportunities. As production scales, we pass savings to customers—not extract maximum margin.
An open-source deep-sky observatory with hardware assembled and software in active development. Three co-aligned optical channels will capture color images, photometric time-series, and hydrogen emission maps simultaneously. We're seeking software engineers, sponsors, and observatory hosts to help bring this to production.
All three optical channels are co-aligned on the same deep-sky target. This is our current prototype specification—subject to change as development progresses.
┌─────────────────────────────────────────────────────────────────┐
│ HERALD DSMO OPTICAL TRAIN │
│ (Prototype Spec) │
└─────────────────────────────────────────────────────────────────┘
CHANNEL 1: DEEP-SKY IMAGING (Master/Pointing Authority)
═══════════════════════════════════════════════════════
┌──────────────────┐ ┌──────────────┐
│ Maxvision 102ED │────▶│ Poseidon-C │
│ 102mm f/7 APO │ │ IMX533 │
│ FL: 700mm │ │ 9MP Color │
└──────────────────┘ │ Cooled -35°C│
└──────────────┘
FOV: ~0.93° × 0.93° • Plate scale: 1.11"/px • Dictates pointing direction
CHANNEL 2: BVRI PHOTOMETRY (Science)
════════════════════════════════════
┌──────────────────┐ ┌───────────┐ ┌──────────────┐
│ Askar FRA400 │────▶│ EFW Mini │────▶│ Ares-M Pro │
│ 72mm f/5.6 │ │ 5-pos │ │ IMX533 │
│ FL: 400mm │ │ BVRI │ │ 9MP Mono │
└──────────────────┘ └───────────┘ │ Cooled -35°C│
└──────────────┘
FOV: ~1.6° × 1.1° • Plate scale: 1.94"/px • AAVSO-compatible output
CHANNEL 3: H-ALPHA NARROWBAND
═════════════════════════════
┌──────────────────┐ ┌───────────┐ ┌──────────────┐
│ SVBony SV106 │────▶│ H-alpha │────▶│ Ares-M Pro │
│ 60mm f/4 │ │ 7nm │ │ IMX533 │
│ FL: 240mm │ │ 656.3nm │ │ 9MP Mono │
└──────────────────┘ └───────────┘ │ Cooled -35°C│
└──────────────┘
FOV: ~2.7° × 2.7° • Plate scale: 3.23"/px • Hydrogen emission mapping
These specifications represent our current development target based on prototype testing. Component selection, optical train design, and mechanical packaging are all subject to change as we iterate. We're actively seeking collaborators with optical engineering, mechanical design, and embedded systems experience.
Park on any deep-sky target and Herald's three channels work simultaneously— color imaging, stellar photometry, and hydrogen emission mapping from a single pointing.
Poseidon-C with 102mm f/7 APO captures true-color portraits of nebulae, galaxies, and star clusters. Hours of integration produce stunning images while the other channels capture parallel science.
Ares-M Pro cycles through BVRI filters measuring every star in the field. Time-series photometry catches eclipsing binaries, pulsating variables, flare stars, and potential exoplanet transits.
Ares-M Pro with 7nm narrowband filter captures continuous hydrogen emission at 656.3nm. Maps nebula structure invisible in broadband while Poseidon-C and the photometry channel work in parallel.
Automated stacking, photometric reduction, and image processing. Edge compute handles camera coordination while cloud or local GPU runs deep analysis on accumulated data.
Herald will integrate battle-tested open-source engines under a unified orchestration layer. This architecture is in active development—we're seeking software engineers to help build it.
┌─────────────────────────────────────────────────────────────────────────────┐
│ USER INTERFACE LAYER │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │
│ │ Web Dashboard │ │ Mobile App │ │ CLI Tools │ │
│ │ (React) │ │ (Future) │ │ (Python) │ │
│ └────────┬────────┘ └────────┬────────┘ └────────┬────────┘ │
└───────────┼─────────────────────┼─────────────────────┼──────────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ ORCHESTRATION LAYER │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ THE AGENT (Central Coordinator) │ │
│ │ • Session scheduling • Filter wheel timing │ │
│ │ • Multi-channel sync • Data flow management │ │
│ │ • Exposure coordination • Error handling │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ PROCESSING PIPELINES │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │
│ │ COLOR IMAGING │ │ PHOTOMETRY │ │ H-ALPHA │ │
│ │ Pipeline │ │ Pipeline │ │ Pipeline │ │
│ │ │ │ │ │ │ │
│ │ • Debayer │ │ • SEP/AstroPhot│ │ • Calibration │ │
│ │ • Stacking │ │ • BVRI Calib │ │ • Stacking │ │
│ │ • Stretching │ │ • Time-series │ │ • Continuum │ │
│ └─────────────────┘ └─────────────────┘ └─────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ EDGE LAYER (Pi 5) │
│ ┌────────────────┐ ┌────────────────┐ ┌────────────────────────────┐ │
│ │ INDI Server │ │ Hailo-8L │ │ Storage Manager │ │
│ │ Camera control│ │ ML inference │ │ Dual NVMe RAID │ │
│ └────────────────┘ └────────────────┘ └────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ EXTERNAL SERVICES │
│ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ │
│ │ Astrometry.net │ │ AAVSO Upload │ │ Cloud Storage │ │
│ │ Plate solving │ │ Photometry DB │ │ (Federated) │ │
│ └─────────────────┘ └─────────────────┘ └─────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
Three cameras capturing different data simultaneously requires coordination. The Agent manages filter wheel timing, exposure schedules, and data flow between channels. It ensures Ares completes its BVRI cycle while Mars integrates and Ceres captures continuous H-alpha—no conflicts, optimal throughput.
Each pipeline runs established, community-vetted software. Image stacking uses proven algorithms. Photometry uses SEP or AstroPhot for BVRI reduction. Astrometric solutions use Astrometry.net. We orchestrate—we don't replace what already works.
A dedicated Raspberry Pi 5 with 16GB RAM and Hailo-8L AI accelerator (13 TOPS) handles camera control, filter wheel sequencing, and frame buffering. Dual NVMe storage holds raw FITS data locally. This proven architecture ensures reliable autonomous operation.
Heavy processing happens after capture. In Federated mode, data uploads to cloud infrastructure for stacking, photometric reduction, and multi-station combination. In Sovereign mode, raw FITS streams to your local network—bring your own GPU for custom processing pipelines.
Herald DSMO is in active development. These milestones are targets, not commitments— timelines will shift as we learn and iterate.
Single-channel prototype using guide scope. Validated basic capture workflow, tested camera control software, established baseline image quality.
Finalized optical train specifications, ordered production components, designed mechanical integration. Three-channel architecture defined.
Hardware assembled. Now developing weatherproof enclosure and control software. Testing optical alignment, validating photometric accuracy against known standards. Seeking software engineers.
5-10 beta units deployed to collaborators for real-world testing. Iterate on mechanical design, refine software, establish operating procedures.
First production run of 50 units. This timeline is aspirational and depends on development progress, component availability, and funding.
We believe in radical transparency. Here's our current BOM estimate—these numbers will change as we negotiate volume pricing and finalize component selection.
This BOM represents raw component costs at small-quantity pricing. Not included: assembly labor, quality testing, calibration time, shipping, support infrastructure, warranty reserves, or any margin. Final retail pricing has not been determined and will depend on production volume, supplier negotiations, and operational costs. We're sharing this to be transparent about our development process.
All three cameras are co-aligned on a tracking equatorial mount. Poseidon-C targets a specific deep-sky object and dictates pointing. The first Ares-M Pro captures BVRI photometry on stars in that field. The second Ares-M Pro captures continuous H-alpha emission data. Three complementary datasets from one pointing, all with cooled IMX533 sensors.
Power Users: All raw FITS data accessible via local network API. Bring your own GPU rig for custom ML pipelines—the Pi handles autonomous operation while your hardware runs experimental analysis.
Herald DSMO is in early development. We're looking for engineers, sponsors, observatory hosts, and beta testers to help bring this project to production.
Help us build it
Fund open-source science
Target Q3 2026
Sponsor multiple stations or contribute equipment to build the founding network. Your brand on research stations across North America.
Fund multiple stations for institutions and schools. Recognition on each station, in the Founding Network, and on our website. Tax-deductible STEM contribution.
Get your gear into 25+ educational institutions. Donate components at cost or fund complete stations. Students learn on your equipment.
Donate cameras, optics, filters, or other components. We handle assembly, delivery, and support. Your contribution recognized on every station.
STEM education grants, science outreach funding, workforce development programs. Herald stations deliver measurable educational outcomes.
Pool resources to sponsor a station for your local school or science center. Group recognition for your organization.
Real testimonials from educators and researchers. Students becoming lifelong customers. Press coverage of your STEM investment. Concrete impact, not just a logo.
Herald uses a split-brain architecture: time-critical decisions happen locally with zero latency, while deep analysis can leverage cloud compute. You control what stays on your machine.
Camera control, filter sequencing, and frame buffering run entirely on the Pi 5. Exposure timing is critical for photometry—there's no time for round-trips. Local means reliable.
All processing local. Deep analysis runs on your GPU after capture. Data never leaves your machine. GPU requirements TBD after final optimization and testing.
Edge operations local, deep analysis cloud-assisted. Stacking, photometric reduction, and multi-station data combination. Free forever. Contribute to open science.
Last night, 47 stations captured data. Cloud processing combines photometry across the network. Multi-station observations improve precision and coverage.
Switch anytime. Export everything. No lock-in. We believe your observations belong to you—always.
Federated mode offloads heavy analysis to the cloud. Edge operations run lean. No high-end GPU required to contribute real science.
All Herald software is 100% open source. Transparent development, auditable algorithms, and a global network of citizen scientists advancing space observation together.
Herald DSMO (Deep Space Measurement Observatory) is a deep-sky observatory currently in early development. The goal is three co-aligned optical channels that capture color images, calibrated BVRI photometry, and H-alpha emission maps simultaneously. We're seeking collaborators to help bring this from prototype to production.
Sovereign mode runs all processing locally—data never leaves your machine. Federated mode keeps edge operations local but uploads captured data to cloud servers for stacking, photometric reduction, and multi-station combination. Both modes use the same architecture where camera control and frame buffering always happen locally on the Pi 5.
None required. Herald includes a dedicated Raspberry Pi 5 (16GB) with Hailo-8L AI accelerator that handles all camera coordination and autonomous operation. Federated mode uploads data to cloud for stacking and photometric reduction. Power users wanting custom ML pipelines can tap raw FITS data via local network API and run their own GPU rig (RTX 5090, etc.) in parallel—the edge system keeps running independently.
Yes, 100% of Herald software is open source. This includes the Agent (orchestrator), all integrations with existing tools (Skyfield, SEP, AstroPhot, Astrometry.net), and the processing pipeline. Every algorithm is auditable and you can modify anything.
Hardware is assembled but enclosure and software are still in early development. We're targeting beta testing in Q1-Q2 2026 and a founding network launch in Q3 2026—but these timelines are aspirational and subject to change based on development progress and funding. We're not accepting pre-orders or deposits at this time.
Herald DSMO is in active development. Join our mailing list for project updates, prototype results, and announcements about beta testing and collaborator opportunities. No spam—just meaningful progress reports.
Collaborators, future beta testers, potential sponsors, and interested observers all welcome.