Purifier Placement Test
When moving, rearranging a room, or facing smoke, use one sensor for a short test to find the purifier location, outlet direction, and door-closing setup that clears particles fastest.
After moving, rearranging furniture, or during a smoke event, the user selects their purifier model and places a portable air-quality monitor in the center of the room. The app first asks them to measure a baseline with doors and windows closed and fan speed held constant. It then guides them through placing the same purifier in two or three candidate locations, running each location for the same number of minutes.
After each round, the app plots the particle-reduction rate as a simple curve, making it clear which location clears particles fastest and which is affected by door gaps or HVAC supply airflow. Users can also note whether a door was open, the AC was running, or people were moving through the room. The final result recommends the best placement, outlet direction, and any door to close or furniture to move.
The first version answers only where to place one purifier in one room; it does not present short-term measurements as a whole-home air diagnosis. Users can retest the same candidate locations when the season changes, they replace a sofa, or the HVAC airflow direction changes.
Why now
As observed on August 5, AirProof AI ranked fourth in Product Hunt’s new-product feed, making purifier placement a direct interactive problem. S1 That makes users who have just moved, rearranged furniture, or encountered smoke more likely to ask exactly where their purifier should go in their own room. S1
Target user
Primary users are renters and households that already own an air purifier and a portable particle monitor. A move, new furniture, or a change in HVAC airflow can invalidate their previous placement assumptions. During smoke events, they do not want to spend days relying on subjective impressions to find the right setup. They need to compare candidate locations quickly in one room and retain evidence they can retest.
Minimal entry point
The first release accepts timestamped PM2.5 data exported from a sensor and also allows manual readings. It can begin by supporting AirVisual Pro export files. S4 The browser reads CSV files through its file interface and stores experiment records locally. Each round marks the purifier start time, then fits a decline slope to the logarithm of particle concentration. The baseline round estimates natural settling, while candidate locations are compared only on their adjusted decay rates. It will not initially simulate room airflow or claim to provide health diagnoses. The model catalog stores only the model name, fan-speed setting, and user notes, avoiding dependence on incomplete device specifications.
Punching above its weight
Recruit the first users through air-purifier forums, smoke-event mutual-aid groups, and communities of portable-sensor users. Publish before-and-after curves from moving a purifier within the same room, rather than generic placement advice. Create export guides for several common sensors to reach people already searching for ways to analyze their data. Let users generate anonymous comparison charts to share directly in placement discussions.
Competitors & gaps
- AirProof AIGoogle
- AirProof AI lets users choose a preset room, drag a purifier into place, and view predicted airflow. Its advanced features can also automatically identify positions with better coverage. S2 Its advantage is that users can compare multiple placements in seconds without a sensor. Its public pages mainly show standard room layouts and simulated results, rather than measured calibration in a user’s own room. When furniture gaps, door and window conditions, or HVAC airflow differ from the presets, the predictions may not explain real-world differences. The opening for the Purifier Placement Test is a short, controlled comparison using the same purifier and sensor. It does not need to outperform airflow simulation; it only needs to answer which candidate location clears particles faster in the current room. The two can also complement one another: simulation narrows the candidates, then measurement confirms them.
- IQAir AirVisual ProGoogle
- IQAir AirVisual Pro measures indoor PM2.5 and displays real-time and historical data in its app. Device data can also be exported for users to analyze themselves. S4 It already handles continuous monitoring, trend viewing, and anomaly alerts. Users can observe changes after opening windows, cooking, or running a purifier. The gap is that its charts are not structured as placement-comparison experiments. Users still need to remember when they moved the purifier, its fan speed, and door or window conditions, then decide whether two decline periods are comparable. The Purifier Placement Test can build on existing data rather than creating another sensor. Timed steps, condition checks, and a consistent score turn monitoring data into a placement conclusion. Supporting only one export format at launch limits coverage, but allows the analysis workflow to be made robust first.
How it makes money
The free version includes one single-room comparison test. A one-time paid upgrade unlocks multi-room profiles, historical retest comparisons, and shareable reports. It will not charge by purifier model initially, so maintaining the device catalog does not become the main cost.
The case against
Short-term curves can be easily skewed by sensor noise and differences in starting concentration. Foot traffic, an open door, or HVAC cycling can make candidate locations incomparable. Controlling these variables requires a baseline round and multiple waiting periods, which may feel cumbersome. If the app presents an overly certain best location, users may mistake random variation for a stable conclusion. Different sensor sampling rates and export formats will also create ongoing integration costs. The product must show data quality and repeat-test results; otherwise, one incorrect recommendation could undermine trust.