
ParkSense AI
A palm-sized edge box that plugs into your existing parking cameras.
- Counts free bays in real time
- Flags overstays and wrong parking
- Guides drivers to open spaces
From $499 per edge box
DetailsRetrofit forklift camera that warns drivers before they hit someone
Software: $15–$25 per month per forklift
Concept, not for sale yet. Tell us if you want it; that decides what we build.
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How it fits together
Scroll or tap a part. Press “See the 3D CAD design” to watch the model, built from our CAD, light each part up and show how it connects.

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01
The whole ForkGuard AI
A camera on the forklift guard spots people behind the truck and chimes the driver in under 300 ms; an impact sensor logs rack hits.
02Brain
Raspberry Pi Zero 2 W
The brain: it runs the fg-vision, fg-imu, fg-io program

03
AI Camera (IMX500)
Finds people behind the truck, on the sensor itself
Raspberry Pi Zero 2 W · CSI-2 ribbon cable · Person boxes, no images

04
Impact sensor
Feels hits at 400 Hz and wakes the logger
Raspberry Pi Zero 2 W · I²C and GPIO 4 interrupt · Acceleration, impact wake
05
Cab LED bar
Shows ready, check due or a red warning flash
Raspberry Pi Zero 2 W · GPIO 18, level shifter · LED colour data
06
Cab piezo chime
Gives a three-beep warning to the driver
Raspberry Pi Zero 2 W · GPIO 13 PWM and MOSFET · 2 kHz chime drive
07
Cab mute button
Driver presses to mute the chime for 10 s
Raspberry Pi Zero 2 W · GPIO 27 pin · Button press
08
Truck power converter
Turns truck battery power into 5 V for the unit
Raspberry Pi Zero 2 W · 5 V on M12 cable · 5 V power
09
All connected
7 key parts, one program, and your phone
What it is
A rugged camera for the forklift roof with an in-cab display that warns of pedestrians.
What it does
Who it's for
Warehouses, 3PLs, factories, builders' merchants and retail distribution centres.
The idea
The problem today
Small warehouses with 5 to 40 mixed-brand forklifts find rack and door damage days later, with no idea which truck or shift did it. Near misses behind a reversing truck are never written down, so nobody sees the hotspot until someone is hurt. The OSHA daily pre-shift check is a paper sheet that is often skipped or filled in at the end of the week.
With ForkGuard AI
A camera unit on the back of the overhead guard and a cab pod log every impact and every person close behind a reversing truck, and chime in the cab as a driver aid. The driver scans a tag on the truck to do the pre-shift check on a phone. The manager sees impacts, near-miss hotspots and check compliance for every truck on one dashboard. It never slows or stops the truck.
How the parts connect
Every part, what links it to the brain, and how the data reaches your phone. A solid line is a cable; a dashed line is a radio link.
The program
camera.on('detections', boxes => {
const people = tracker.update(boxes.filter(b => b.score >= 0.45));
const bands = people.map(p => distanceBand(p.footPoint)); // danger, close, near
const near = bands.some(b => b !== 'near');
if (io.reverse && motion.moving && near) {
if (++closeFrames >= 3 && !muted) io.chime(), io.led('red-flash');
} else closeFrames = 0;
if (near) db.insert('nearmiss', { band: closest(bands), zone });
});
imu.on('sample', a => {
if (highPass(a) >= 3.0 && lasted(5)) db.insert('impact', peak());
});
setInterval(() => agent.flush(db, mqtt), 1000); // when Wi-Fi is upTo your phone
Supervisor phone or laptop browser
One screen for each job ForkGuard AI does.
Reversing near missFL-07 backs out of aisle 14 as a picker steps behind it. The cab chimes and flashes red as a driver aid, and the near miss is logged.
Impact logA truck clips a rack upright. A minute later the supervisor has a text, so the damage is found and checked the same shift.
Pre-shift checkBefore each shift the driver scans the truck's QR tag and works through the daily check on a phone. A truck with no check shows amber.
App screens with sample data. The interface is in development.
| Impact event | 4.1 g, major | Each hit |
|---|---|---|
| Near-miss | Close band, aisle 14 | Each reverse event |
| Shift summary | 266 min moving, 1 impact | Each key-off |
| Pre-shift check | Pass, FL-07 | Each shift |
| Unit health | READY, 12 fps | Every 5 min |
Video is not recorded or sent. Only events, with the truck and zone, are stored.
CAD design · Design complete (stages 1-6), not built

| AI processor | Hailo-8L (13 TOPS) + ARM host in the camera unit |
|---|---|
| Camera | Wide-angle 1080p camera (~150° HFOV) with IR illumination for dark aisles; optional rear camera |
| Sensors | IMU for motion and impact detection · Ambient light sensor |
| Connectivity | Wired link to cab display · Wi-Fi 6 for near-miss upload · Optional LTE · Digital output for truck speed-limit input (where supported) |
| Power | 12–80 V DC forklift supply with isolated converter, ~6 W (target) |
| Enclosure | Black rugged IP67 camera unit on overhead-guard clamp; in-cab display with buzzer and LED bar |
| Dimensions | Camera unit 14 × 8 × 6 cm; cab display 10 × 7 × 3 cm |
| Weight | Camera ~600 g; display ~200 g |
| Ingress rating | IP67 camera unit; IP54 cab display |
| Field of view | ~150° horizontal |
|---|---|
| Range | Up to ~10 m |
| Warning latency | Under 200 ms (target) |
| Low light | IR illumination, works in dark aisles |
| Cab display | Direction and zone indicator |
|---|---|
| Buzzer | Up to 85 dB, adjustable |
| Output | Digital out for speed-limit input |
| Events | Anonymous near-miss log |
| Supply | 12–80 V DC, ~6 W |
|---|---|
| Camera unit | 14 × 8 × 6 cm, IP67 |
| Cab display | 10 × 7 × 3 cm |
| Operating temp. | −25 °C to 50 °C (freezer option planned) |
Targets for production units; they may change during development.
Hardware: $799–$1,099 per forklift (rear camera option)
Software: $15–$25 per month per forklift
Target pricing. Fitting by your forklift service provider or our partner network is quoted per site.
$799 + $15/mo per truck
Forward pedestrian warning with near-miss log.
$1,099 + $25/mo per truck
Adds a rear camera and speed-limit output.
Custom
For multi-site fleets and rental companies.
Indicative launch pricing in USD, excluding taxes and shipping. Final pricing is confirmed before any balance is charged.
Community
ForkGuard AI is in development. Rate the idea, tell us what to change about the features, specs or price, and we'll build it with your feedback.
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Questions
Tell us what this would save you, or ask anything. We reply within two business days.
A member of the IEMI Labs team will reply within two business days.
From the product lab · ideation phase
No. Detection runs on the camera unit and video is not stored. Near-miss events are anonymous: they record time, truck, distance and location, not who was involved. Optional snapshots are blurred on the device before upload.
No. ForkGuard is a driver-assistance warning aid. It does not replace training, traffic management, segregated walkways or the safety measures your regulator expects. Safety-function certification is not claimed.
The camera clamps to the overhead guard, the display mounts in the cab and the harness connects to the truck's 12–80 V supply. Fitting takes about an hour per truck and can be done by your forklift service provider.
Warnings work entirely on the truck with no network. Near-miss events upload over site Wi-Fi when available, or over the optional LTE module.
No. It is a new concept in development. Specifications are target specifications. It is a concept: we are not taking orders, reservations or deposits, and it has no ship date yet.
We are planning a 2-year limited hardware warranty covering manufacturing defects. Final terms will be published before shipping begins.

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