Egocentric Thermostat and Control Wiring Data

Egocentric thermostat and control wiring data is first-person video of a person mounting a thermostat and wiring its controls, recorded from the contributor’s own point of view with synchronized sensor streams alongside. The camera sits on the head, close to what a robot’s onboard camera would see at a wall, so the frames show what the hands are doing to the thermostat, the wires and the terminals rather than a distant view of someone standing near a job. On this site it is a custom collection: you name the task and the setting, and capture is run to a written skill spec.

The catalog describes the task in its own words: "Mount the thermostat, connect control wires to terminals and test the heating and cooling calls." This page repeats that description as written and adds nothing to it. The data is human capture: a paid, consented contributor wears the rig and performs the task. It is not robot or teleoperation data, and it is not a fixed corpus you download.

People reach this topic through several phrasings: thermostat installation robot training data, egocentric thermostat wiring video, an HVAC control wiring dataset, or custom trade service data collection. They describe one request from different angles. Under each of them the work is the same: write down the task, collect it on demand, and receive validated episodes with the labels a training pipeline expects.

The site’s off-the-shelf catalog does not list a thermostat or control wiring dataset, so this is custom collection. It is run as custom collection at scale through a network of thousands of capture providers, for a consistent, recurring data flow to labs. This page does not state a provider count, hours or throughput beyond what the site already states.

One row of the site’s commercial task catalog describes this work: "Thermostat & Control Wiring". It sits in the Construction & Trades sector, in the Trade Service Calls (Plumbing / HVAC / Electrical) environment, whose listed example crews are plumbers, electricians and HVAC crews on service calls at client sites. The row is rated Hard, lists a head-mounted phone or multiview rig as the capture setup, and has the status Ready to deploy. The first table below reproduces it exactly as the catalog states it.

Ready to deploy is the catalog’s own status. The site states elsewhere that the Trade Service Calls rows listed as Ready to deploy have contributors and site access set up. It does not state delivered hours for this row, and this page does not either. The catalog is a list of what is captured or available, not a ceiling on what can be briefed. A thermostat type, wiring step or setting outside the row is a skill-spec question to settle in a Spec Pilot rather than an assumption.

The site does not describe a thermostat brand or model, a terminal designation, a wire-colour convention, a system type or a task duration for this row, so none is stated here. The three rows beside it in the same environment are shown in the table for comparison: two outlet wiring rows and HVAC equipment installation. Each is a different job and this page does not count them as thermostat work.

Each attempt is delivered as one episode. For the instrumented tier the site describes a head-mounted stereo rig that records first-person RGB, with a metric depth stream recovered from the calibrated stereo rig rather than from a standalone depth sensor, and 6-DoF IMU data at 200 Hz from head- and wrist-mounted sensors. The wider stack is ten streams: a 4K head camera, two wrist cameras, depth, IMU, 3D hand and body pose, instance segmentation and action labels, hardware-aligned under 2 ms. The catalog lists a head-mounted phone or multiview rig for the thermostat row. Which tier a program uses is set in the skill spec.

Hand pose is delivered for both hands as 21 joints per hand in three dimensions, with a per-joint visibility flag for occluded fingers. Connecting control wires to terminals is the kind of step where a hand closing around a wire or a terminal hides fingers, and the flag marks the joints that were not visible instead of presenting a guess as a measurement. Contact events mark when a hand meets the item.

Every stream is hardware-triggered onto one PTP clock domain, so depth, motion and hand pose line up with the same video frame rather than being approximated afterwards. The rig is calibrated twice per session, and an episode is accepted only if RMS reprojection stays under 0.28 px.

The only language field the site ties to Firsthand capture is one task instruction per episode. The site does not list a temperature, voltage, current or controller-signal stream for this row. This is human first-person capture, not robot or teleoperation data.

Inside each episode, action segments divide the timeline into spans, each carrying start_ns, end_ns, verb and noun. For this task a segment can be one step as written in the skill spec, such as mounting the thermostat, connecting the control wires to the terminals, and testing the heating and cooling calls, so one job becomes a sequence of labeled steps rather than one long clip. The other standard fields are hand_joints and hand_visible for 3D hand pose, contact_events, objects, and per-frame instance masks where the spec calls for them, stored at the depth resolution of 848×480 so they line up with the depth stream.

Delivery is in the format your stack already reads: RLDS, LeRobot, WebDataset, HDF5, zarr or Rerun .rrd, or raw streams with metadata. The official sources describe three of these in their own terms. The RLDS repository describes an ecosystem of tools to store, retrieve and manipulate episodic data, including for learning from demonstrations and imitation learning. The LeRobot repository describes its dataset format as synchronized MP4 videos or images for vision plus Parquet files for state and action data. The WebDataset repository describes tar files in which files that belong together share the same basename and make up a training sample. In the HDF5 layout the site documents, hand pose sits at annotations/hand_joints and action segments at annotations/action_segments.

The site does not list labels for the quality of the wiring job. There is no stated label for whether a connection is correct, whether a terminal is secure or whether the heating and cooling test passed. The verb and noun on each action segment is the vocabulary the skill spec defines with you, and anything beyond it is a scoping conversation, not a delivered field. Firsthand also offers MCAP delivery, and the stereo HVAC page covers it for the same family of rows.

Four existing pages touch the thermostat row, and none is dedicated to it. The egocentric HVAC service page covers five HVAC-related rows as a task family and lists the thermostat row as one of them. The stereo HVAC page covers the same five rows with a calibrated stereo pair and MCAP delivery. The egocentric electrical work page covers five electrical rows and leaves the thermostat row out, calling it a heating and cooling control task. The cable routing and wiring page covers routing, clipping, patching and crimping across benches, racks and venues, and lists the thermostat row among its wiring rows.

This page is narrower than all four. The subject here is the one Thermostat & Control Wiring row: mount, connect and test, captured first-person. The second table below sets the four pages side by side. For any of them the statuses are the catalog’s own, and no page states delivered hours for the row.

The failure modes the site already describes apply directly. Close two-handed work hides fingers behind terminals and wires, which is why hand pose carries a per-joint visibility flag. A thermostat or wire that leaves the frame too long breaks an episode, which is why an item is rejected when the manipulated object is out of frame for more than 15 percent of the episode. Invalid depth over more than 35 percent of the manipulation region is also a reject, and so is an undocumented bystander.

On the stereo tier the site states that glare makes single-frame depth worse, that depth degrades on wet and reflective surfaces, and that confidence maps mask low-confidence regions. Lighting and enclosed-space handling for the thermostat row are Not stated, so raise them in the spec. A human reviewer then checks each episode against the task spec, and a reject log ships with each batch.

The GR00T N1 paper structures its training corpora as a data pyramid. In its words: "large quantities of web data and human videos lay the base of the pyramid; synthetic data generated with physics simulations and/or augmented by off-the-shelf neural models form the middle layer, and real-world data collected on the physical robot hardware complete the top." In that framing, first-person human video of a trade task would belong to the human-video base. Human capture does not replace robot data, and this page does not claim that it does.

The same paper says of the human video datasets it used: "These do not include explicit action labels but contain extensive sequences of human-object interactions." That is a statement about those datasets, not about this one. A Firsthand episode carries labeled action segments, 3D hand pose and contact events, so the structure of the step is explicit in the data. No model named on this page was trained on Firsthand data, and this page does not suggest otherwise.

Thermostat wiring is a useful task to specify because it is made of small, ordered, close-contact steps: mount, connect, test. This page does not claim that any robot performs thermostat installation, that any model improves from this data, or any result. A custom collection lets you aim at the step your model is missing instead of hoping a public release contains it, and have it captured, labeled and checked to terms you agreed.

The catalog names the setting for this row as the Trade Service Calls environment, with plumber, electrician or HVAC crews on service calls at client sites. The site does not state whose premises the row is recorded on, how a site is arranged, or whether the row is recorded on a live job or on a staged set, so this page does not either. It also does not state regions or cities for the row.

Every contributor signs a written release before capture, and each delivered episode links to that record through consent artefact IDs in the batch data card. At ingest, automated detection finds faces, plates and screens and blurs them irreversibly, and speech is scrubbed of names, addresses and card numbers. A human reviewer confirms that no un-consented person is identifiable in any frame, and footage that cannot be de-identified is discarded. The anonymization record is delivered with the data.

On safety, the site states nothing about electrical safety, code, licensing, qualification or certification for the thermostat row, and this page makes no such claim. Two outlet wiring rows in the same environment mention a voltage tester, and one says with power off. The thermostat row does not state a power state, and this page says no more than the row does. If your program needs terms about premises, access or who may be in frame, raise them when you scope it. None of this is legal advice, and the executed agreement controls.

From signed spec to first validated batch, the site states a median of 48 hours where coverage is deep and three to four weeks where it is thin and contributors need to be recruited first. The site does not state which of those applies to this row, so that is settled in your quote. Speed comes from a warm pipeline, not from cutting consent, review or anonymization. After the first batch, on-demand top-ups run against the same accept criteria, and the site does not state a turnaround for those later batches.

The site also states program milestones: a pilot reaches its first delivery in two to three weeks, and a standing program reaches full rate in four to six weeks. Those assume capture coverage is already in place. Batch size is Not stated and is quoted against your spec.

Validation runs against signed accept criteria written into the spec before capture. An episode is rejected for a sync breach beyond the ceiling for more than three consecutive frames, calibration drift beyond tolerance, the manipulated object out of frame for more than 15 percent of the episode, more than 35 percent invalid depth pixels in the manipulation region, an undocumented bystander, or a mismatch against the named skill spec. Only footage that clears the criteria is billed as a validated hour, and rejected items are recaptured at the provider’s cost.

The license is perpetual, irrevocable and worldwide, with the data buyer-owned and non-exclusive by default. Training, evaluating, fine-tuning and deploying models, including commercial ones, is permitted, and exclusivity is available as a separate term. The executed agreement controls. The site does not publish a price list, a minimum order or a batch size for this task, so those are set in your quote.

Describe the steps, the setting and the failure or variation cases your pipeline is missing. That becomes a written skill spec, quoted for reach, timeline and price before any capture begins, and most programs run a Spec Pilot first: a small, fast first batch that proves the spec and the accept criteria on real footage before volume scales. A published sample recording is on the sample data outputs page if you want to see the streams before you write a spec.

Three choices matter most. Name the step and the item rather than a broad activity, using the catalog wording "Mount the thermostat, connect control wires to terminals and test the heating and cooling calls", because that is what lets each step become one action segment. Decide what counts as one attempt, since the site does not set that length. And write the reject rule and the acceptance test first, so the batch is judged against terms you agreed.

Where this site does not state something, this page says "Not stated" rather than filling the gap. The final table separates what is delivered from what is not stated. There is no stated label for connection correctness or test outcome, no temperature or controller-signal stream, no safety, code, licensing or certification position, and no thermostat brand, terminal designation or wire-colour convention. Counts of episodes, hours, sites and contributors are not fixed numbers on this site. They are set in your skill spec.

The tradeoff to plan for is the embodiment gap between a human hand and a robot end-effector, which retargeting or pairing with robot data has to close. What you get is human first-person demonstrations in which the hands, the work and the step structure are explicit.