docs(seo): SPARROW content depth + long-tail (edge/field lane)

docs/build_mkdocs.md

@@ -7,7 +7,7 @@ tags:
   - developer-guide
 ---
 
-# Developer Guide — Building the Docs
+# Developer Guide: Building the Docs
 
 This page explains how to build and preview the SPARROW documentation site locally.
 
@@ -37,7 +37,7 @@ To build the static site without serving it:
 mkdocs build
 ```
 
-Output goes to `site/` (gitignored — never commit this directory).
+Output goes to `site/` (gitignored, never commit this directory).
 
 ## Deploy to GitHub Pages
 

docs/cite.md

@@ -1,5 +1,5 @@
 ---
-description: "How to cite SPARROW — software citation and BibTeX entry for the SPARROW edge AI wildlife monitoring system by Microsoft AI for Good Lab."
+description: "How to cite SPARROW: software citation and BibTeX entry for the SPARROW edge AI wildlife monitoring system by Microsoft AI for Good Lab."
 tags:
   - SPARROW
   - citation

docs/edge-ai-wildlife-monitoring.md

@@ -0,0 +1,67 @@
+---
+title: "Edge AI Biodiversity Monitoring with SPARROW"
+description: "SPARROW is a solar-powered edge AI wildlife monitoring device that runs detection on-device on an NVIDIA Jetson and uplinks results over Starlink."
+tags:
+  - edge-ai
+  - wildlife-monitoring-device
+  - SPARROW
+  - biodiversity
+  - jetson-orin-nano
+  - remote-monitoring
+---
+
+# Edge AI Biodiversity Monitoring with SPARROW
+
+SPARROW is a wildlife monitoring device that brings AI to the field instead of sending raw data home for processing. A unit sits in the landscape, gathers images and sound from its sensors, runs the AI on the spot, and sends only the results back. That design is what makes biodiversity monitoring practical in places with no grid power and no cell coverage.
+
+This page explains what edge AI buys you for conservation fieldwork, who SPARROW is built for, and how its on-device approach differs from a traditional camera-trap-plus-cloud pipeline.
+
+## Why run the AI at the edge?
+
+Most camera-trap workflows collect images first and analyze them later, often weeks after retrieval. SPARROW inverts that order. Each unit carries an NVIDIA Jetson Orin Nano that runs the models locally, so detection and species classification happen within minutes of capture rather than after a field season ends.
+
+Doing the work on-device has three practical payoffs in remote deployments:
+
+- **Bandwidth that fits a satellite link.** Running inference locally means only detections and metadata travel over the network, not gigabytes of raw frames. That keeps a low-Earth-orbit uplink usable even where bandwidth is scarce.
+- **Insight while it still matters.** Because results arrive in near real time, a poaching event or a rare-species sighting can surface the same day instead of after the cards come back from the field.
+- **Privacy before anything leaves the box.** SPARROW screens for human images on-device and removes them before upload, so sensitive frames never enter the pipeline.
+
+## What a SPARROW unit is
+
+A SPARROW unit is a self-contained, solar-powered enclosure that combines sensing, compute, power, and connectivity in one weatherproof box:
+
+- **Sensing.** Up to 150 solar WiFi camera traps, an AudioMoth acoustic sensor, and I²C environmental sensors for temperature, humidity, and pressure.
+- **Compute.** An NVIDIA Jetson Orin Nano serving models through NVIDIA Triton Inference Server.
+- **Power.** Solar panels feeding a LiFePO4 battery through an MPPT charge controller, with scheduling that keeps the unit running through nights and cloudy stretches.
+- **Connectivity.** A Starlink Mini satellite uplink for sites beyond cellular or WiFi reach.
+
+For the full parts list and how the pieces fit together, see the [hardware and architecture](hardware.md) page.
+
+## Who SPARROW is for
+
+SPARROW is aimed at researchers and conservation teams who need to monitor wildlife where the usual infrastructure does not reach:
+
+- **Field ecologists** running long, unattended deployments far from power and roads.
+- **Protected-area managers** who want detections surfaced quickly rather than after retrieval.
+- **Conservation technologists** who would rather assemble from a documented bill of materials than build an edge stack from scratch.
+
+If a site has reliable mains power and a wired or cellular connection, a simpler camera-trap setup may be enough. SPARROW earns its complexity precisely where that infrastructure is missing.
+
+## The AI that runs on the device
+
+SPARROW serves wildlife models built on [PyTorch-Wildlife](https://github.com/microsoft/Pytorch-Wildlife), exported to ONNX and run through Triton on the Jetson GPU. The default deployment ships with three models: MegaDetector v6 for animal, person, and vehicle detection, an Amazon Basin species classifier, and a bird-specific detector. The [software setup](setup.md) page covers how those models are deployed and served.
+
+## Where to go next
+
+- **[Hardware and architecture](hardware.md)**: components, power, connectivity, and how the system is wired together.
+- **[Field deployment guide](field-deployment.md)**: siting, power planning, connectivity, and maintenance for a remote install.
+- **[Limitations and field considerations](limitations.md)**: the conditions that constrain an autonomous, off-grid unit.
+- **[Software setup](setup.md)**: the one-click Jetson script, Docker stack, and AI models.
+
+## Related Microsoft biodiversity AI projects
+
+SPARROW is the field-hardware layer of a larger open-source toolkit from the Microsoft AI for Good Lab. The [Microsoft Biodiversity hub](https://microsoft.github.io/Biodiversity/) ties the ecosystem together.
+
+- **[MegaDetector](https://microsoft.github.io/MegaDetector/)**: the camera-trap detector that locates animals, people, and vehicles in images; SPARROW runs it on-device.
+- **MegaDetector-Acoustic (documentation coming soon)**: the project that analyzes and classifies audio recordings; SPARROW collects sound in the field and leaves audio classification to it.
+- **[PyTorch-Wildlife](https://microsoft.github.io/Pytorch-Wildlife/)**: the AI framework whose detection and classification models SPARROW packages for the edge.

docs/field-deployment.md

@@ -0,0 +1,74 @@
+---
+title: "Remote Wildlife Monitoring: SPARROW Field Deployment Guide"
+description: "Plan a remote wildlife monitoring deployment with SPARROW: siting, solar power, Starlink wildlife connectivity, camera-trap networking, and field maintenance."
+tags:
+  - remote-wildlife-monitoring
+  - field-deployment
+  - starlink
+  - solar-powered
+  - SPARROW
+  - camera-trap
+---
+
+# Remote Wildlife Monitoring: SPARROW Field Deployment Guide
+
+Getting a SPARROW unit to run unattended for months in a remote location is mostly a planning problem. This guide walks through the field-side decisions: where to put the unit, how to size its power, how its connectivity behaves over Starlink, how to lay out the camera-trap network, and what maintenance looks like once it is live.
+
+It assumes the unit is already built and flashed. For parts and wiring see [hardware and architecture](hardware.md); for the software stack see [software setup](setup.md).
+
+## Siting the unit
+
+The SPARROW enclosure has to satisfy three things at once: sun for the panels, sky for the satellite dish, and radio reach to the cameras.
+
+- **Sun exposure.** The solar panels are the unit's only power source, so the mounting spot needs as much unobstructed daylight as the site allows. The 45-inch tilt brackets let you angle the panels toward the sun's seasonal arc.
+- **Clear sky for Starlink.** The Starlink Mini dish needs an open view overhead to hold a link to the low-Earth-orbit constellation. Site it away from dense canopy or terrain that blocks the sky.
+- **WiFi reach to the cameras.** The Jetson runs a WiFi hotspot that the camera traps join, so cameras need to sit within radio range of the enclosure. A long-range outdoor antenna is an option when the camera network spreads out.
+- **Weather and physical security.** The electronics live in an IP65-rated weatherproof junction box built for outdoor field use. Choose a mounting point that protects the panels and dish from the worst of the local weather and keeps the unit out of easy reach.
+
+## Power planning
+
+SPARROW is built to run off-grid indefinitely on solar, but only if power generation and storage are matched to the site.
+
+- **Generation.** Two 100W monocrystalline panels feed an MPPT charge controller wired for a 24V configuration. MPPT tracking squeezes more usable energy out of the panels than a simpler controller would, which matters on short or overcast days.
+- **Storage.** A 24V LiFePO4 battery carries the unit through nights and cloudy stretches. The bill of materials lists a 50Ah to 100Ah cell; pick capacity for your latitude, season, and how much cloud the site sees. Longer dark periods call for more storage.
+- **Demand management.** SPARROW actively manages its own draw. It monitors the charge controller and battery state and schedules components dynamically, throttling or pausing power-hungry tasks to ride out low-charge periods rather than draining the battery flat.
+
+!!! tip "Size for the worst week, not the average"
+    Solar autonomy is set by your cloudiest stretch, not by typical conditions. When in doubt, favor more battery capacity and panel headroom for the darkest part of the deployment season.
+
+## Connectivity over Starlink
+
+SPARROW uses a Starlink Mini kit for its uplink, which is what lets it report from places with no cellular or terrestrial WiFi. Connectivity is treated as intermittent by design.
+
+- **Satellite uplink.** A dedicated `starlink` service watches the satellite link, logs signal metrics, and triggers a data sync when the uplink is up.
+- **Store and forward.** When the link is down the unit keeps working: data is recorded to local storage and synced automatically once connectivity returns, so a connectivity gap does not cost you observations.
+- **Scheduled link windows.** The unit pulls a Starlink sleep-window schedule from the dashboard, so the satellite terminal can be powered down during set hours to conserve energy rather than drawing current around the clock.
+
+Because inference runs on-device, only detections and metadata cross the satellite link, which keeps data volumes within what a remote uplink can carry.
+
+## Camera-trap network
+
+A single SPARROW unit can act as the hub for a sizeable camera network, up to 150 solar WiFi cameras. During setup the Jetson is configured with a persistent WiFi hotspot that the cameras join, and the unit polls them, pulls new images, and deduplicates before running detection. For larger or more spread-out deployments, a higher-gain outdoor WiFi antenna extends the usable range.
+
+## Maintenance and operation
+
+Once a unit is live, most operation is hands-off, but a few things are worth planning around:
+
+- **Pairing and data flow.** The unit pairs to a SPARROW dashboard account with an access key; detections, audio, and system metrics upload there when connectivity allows. Register and obtain a key at [dashboard.sparrow-earth.com](https://dashboard.sparrow-earth.com/).
+- **Health telemetry.** Environmental sensors and system metrics are uploaded alongside detections, giving you a remote read on how the unit is faring without a site visit.
+- **Storage headroom.** A 2TB NVMe SSD buffers images and audio locally so the unit can keep recording through extended offline periods; plan visits or sync windows so the buffer does not fill during a long connectivity gap.
+- **Privacy.** Human images are screened and removed on-device before upload, and the dashboard applies its own scrubbing as a second pass.
+
+## Related pages
+
+- **[Edge AI biodiversity monitoring](edge-ai-wildlife-monitoring.md)**: what SPARROW is and why on-device AI suits remote work.
+- **[Hardware and architecture](hardware.md)**: the components behind every choice on this page.
+- **[Limitations and field considerations](limitations.md)**: the constraints to weigh before committing a site.
+
+## Related Microsoft biodiversity AI projects
+
+SPARROW is part of an open-source biodiversity toolkit from the Microsoft AI for Good Lab; the [Microsoft Biodiversity hub](https://microsoft.github.io/Biodiversity/) is the umbrella for the projects below.
+
+- **[MegaDetector](https://microsoft.github.io/MegaDetector/)**: the camera-trap detection model SPARROW runs on captured images in the field.
+- **MegaDetector-Acoustic (documentation coming soon)**: handles analysis and classification of the audio SPARROW records.
+- **[PyTorch-Wildlife](https://microsoft.github.io/Pytorch-Wildlife/)**: the framework supplying SPARROW's on-device wildlife models.