Food Processing Line Monitoring with LiDARs and AI Vision

Where water, vapor and product meet, count what actually passes.

CRATUS monitors food processing lines with LiDAR and AI vision: item counts, volume, flow and fill levels on belts, flumes, wash tanks, hoppers and kettles. The system is built for the hard cases, where liquids and solids meet, lighting is poor or changing, and the air is full of dust or vapor, and sends results to your line controls and dashboards.

  • One system for
  • LiDAR
  • AI vision
  • Edge
  • Software
AI VISIONLIDARLINE 2COUNT 1,284/minVOLUME 0.42 ft³/ssample valuesWASH TANK, WATER + PRODUCTVAPORILLUSTRATIVE, NOT TO SCALE
Counts + amountsItems, volume and flow
Built forWater, vapor and dust
  • Counts + amountsItems counted and volume measured on the same line
  • Wet, vapor, dustBuilt for conditions where simple sensors fail
  • LiDAR + AI visionShape from LiDAR, appearance from vision
  • Line to dashboardResults to PLC, SCADA and dashboards

The challenge

Why food lines are hard to measure.

Production lines are wet, bright, steamy and fast. The conditions that make food safe to produce make it hard to count.

Wet processing line with tomatoes on a conveyor and a sensor on the frame in bright backlight

Liquids and solids together

Product floats in wash water, tumbles in flumes and arrives wet on the belt. Reflections, splash and foam confuse simple sensors and 2D cameras.

Tomatoes washing in water with a sensor above the stainless steel line

Lighting you can’t trust

Glare on stainless steel and wet product, shadows, mixed lighting and lines that run outdoors change what a camera sees through the day.

Steam rising over a processing line with a sensor mounted above

Vapor, steam and dust

Blanchers, cookers and fryers fill the air with vapor; flour, sugar and spices fill it with dust. Lenses fog and foul, and readings drift.

CRATUS combines LiDAR and AI vision, placed and protected for wet, steamy and dusty lines.

See the approach

Difficult conditions

How each condition is handled.

Every line is different. These are the conditions we plan for.

ConditionWhat goes wrongHow CRATUS handles it
Product in waterReflections, splash and floating productLiDAR and AI vision trained to separate product from water and foam
Glare and wet surfacesBright spots and missing areas in imagesLiDAR unaffected by visible glare; controlled lighting for vision
Low or changing lightCounts drift with time of dayLiDAR brings its own light
Steam and vaporFogged lenses, scattered readingsPlacement out of the plume, purge air and filtering
Dust (flour, sugar, spices)Fouled windows, falling accuracyPurge collars, sealed enclosures and cleaning schedules
Wash-downWater and chemicals on equipmentSealed, washable enclosures rated for wash-down where required
Touching and stacked productItems merge in 2D3D separation with LiDAR plus AI vision

Sensor selection, placement and protection are set per line during the survey.

What we measure

As diverse as the lines we work on.

Counts, amounts and levels across food and beverage processing.

  • Fresh produceTomatoes, potatoes, apples, citrus and more, in flumes, wash tanks and on belts.
  • Meat, poultry and seafoodPortions and pieces on belts, trays and chutes.
  • Bakery and snacksLoaves, buns, chips and fries; volume and spread on the belt.
  • Frozen foodsProduct through freezers and on cold, frosty lines.
  • Nuts, grains and seedsVolume and flow of bulk product on conveyors and in bins.
  • Liquids and saucesLevels in kettles, tanks and hoppers.
  • Packaged goodsPacks, trays and cases counted at the end of the line.
  • Ingredients and dry goodsFlour, sugar and powders in hoppers and bins.

Our approach

From the line to the numbers.

LiDAR, AI vision, edge computing and software, engineered as one system by one team.

Bread rolls on a conveyor with scan zones and an analytics display

Sensing

LiDAR measures shape, height and volume in 3D regardless of light and color. AI vision cameras add appearance: size, color and surface. Each is placed and protected for the conditions on your line.

  • LiDAR for shape and volume
  • AI vision for appearance
  • Purge air and wash-down enclosures

Edge computing

An edge computer at the site merges every sensor into one live picture and computes the analytics locally, so results, not raw sensor streams, leave the site over Ethernet, Wi-Fi or cellular.

  • Multi-sensor fusion on site
  • Analytics computed at the edge
  • Ethernet, Wi-Fi or cellular

Software & integration

Counts, rates, volume and levels per line and per shift on a dashboard, sent to your PLC, SCADA or MES over MODBUS, OPC UA or MQTT, with alerts for jams, gaps and low supply.

  • Dashboard per line and shift
  • MODBUS, OPC UA, MQTT
  • Alerts for jams and gaps

AI

AI separates product from water, foam and the belt, splits touching items, and screens size and appearance, trained on your product and your line.

  • Product vs water and foam
  • Touching items separated
  • Size and appearance screening

What we deliver

Food processing line monitoring.

One line or a whole plant.

Packaged pasta moving along an inclined conveyor with a sensor overhead

Item counting

Produce, portions, pieces and packs counted on belts, chutes and in flumes.

Sensing · AI

Grain pouring from a hopper onto a belt with a sensor mounted above

Volume and flow on belts

Volume and flow rate of bulk product such as fries, chips, nuts and grains.

Sensing · Edge

Sensor above a water flume with a weir in a food plant

Flumes and wash tanks

Product load in water, overflow and feed rate into the next step.

Sensing · AI

Potato chips on a conveyor under a sensor

Hopper, bin and kettle levels

Fill levels of solids and liquids, so supply never runs out unnoticed.

Sensing

Granular product on a belt under a sensor, with a feed chute behind

Gaps, jams and spacing

Empty belt sections, pile-ups at transfers and uneven spread across the belt.

Software · AI

Potatoes on a belt under a sensor in a processing plant

Size and appearance screening

Size distribution and appearance checks with AI vision.

AI

The CRATUS line monitoring system

Sensors and software for wet, steamy and dusty lines.

Sensor types, placement and protection are chosen per line.

CRATUS

LiDAR sensor

Shape, height and volume

  • Unaffected by glare
  • No light needed
  • 3D separation

Measures what is on the belt or in the tank in 3D, regardless of light and color.

CRATUS

AI vision camera

Appearance

  • Size and color
  • Surface checks
  • Trained per product

Adds what LiDAR cannot see: color, surface and appearance.

ASSET-Rx

Edge computer

ASSET-Rx EDGE

  • Sensor fusion
  • AI on site
  • Line-speed results

Fuses LiDAR and vision and runs the AI models at the line.

CRATUS

Enclosures and purge

For wet and dusty lines

  • Wash-down enclosures
  • Purge air
  • Stainless mounts

Keeps sensors clean and sealed where water, vapor and dust are present.

CRATUS

Line dashboard

Per line and shift

  • Counts and rates
  • Volume and levels
  • Alerts

Line data for production, quality and maintenance teams.

CRATUS

Controls integration

PLC, SCADA, MES

  • MODBUS
  • OPC UA
  • MQTT

Sends results into the controls and systems already running the plant.

One system

Sensors, edge, software and AI from one team

CRATUS surveys the line, selects and protects the sensors, trains the AI on your product and integrates results with your controls.

All CRATUS products
CRATUS line monitoringStack
AI
  • Product separation
  • Counting
  • Screening
Software
  • Dashboard
  • Alerts
  • PLC / SCADA
Edge
  • Sensor fusion
  • Models on site
  • Line-speed
Sensing
  • LiDAR
  • AI vision
  • Enclosures

What to send us

These details let CRATUS plan monitoring for your line.

  • Product and what you need: count, volume, flow or level
  • Line type: belt, flume, wash tank, hopper, kettle
  • Line speed and belt width
  • Water, vapor, dust and wash-down conditions
  • Lighting, indoor or outdoor
  • Mounting options above the line
  • Controls the data should reach: PLC, SCADA, MES
  • Photos or video of the line
Send site details

How we work

Surveyed and trained, then installed.

Every line is surveyed for its conditions, and the AI is trained on your product before results go live.

  1. 01

    Line details

    Product, measurement needed, line layout, speed and conditions.

  2. 02

    Survey & sample data

    Sensor selection and placement; sample data collected from your line.

  3. 03

    Train & install

    AI trained on your product; sensors installed with enclosures and purge where needed.

  4. 04

    Commission

    Counts and volumes checked against manual counts or weighed batches.

  5. 05

    Operate & support

    Live line data, alerts and integration, with retraining as products change.

Standards & practices

Designed for food plants.

Equipment over a food line has to meet hygiene, safety and security expectations.

Bread rolls moving under an inspection camera on a bakery line
  • FSMA, 21 CFR 117Current good manufacturing practice and preventive controls
  • HACCPHazard analysis and critical control points
  • 3-A Sanitary StandardsHygienic design of dairy and food equipment
  • EHEDGHygienic engineering and design guidelines
  • IEC 60529Ingress protection, including wash-down ratings
  • NSF/ANSI/3-A 14159Hygiene requirements for processing equipment
  • IEC 60825-1Eye-safe laser classes
  • ISA/IEC 62443Security for industrial networks and devices

Certification is issued by accredited third parties. CRATUS designs and documents installations to these references and supports your food safety plan; we don’t self-certify.

The basics

What can CRATUS measure on a food line?

Counts, amounts and levels: items on belts and in flumes, volume and flow of bulk product, fill levels in hoppers, bins, tanks and kettles, and gaps, jams and spacing on conveyors.

Why combine LiDAR and AI vision?

Each covers the other’s weak spot. LiDAR measures shape and volume in 3D regardless of light; AI vision sees color and surface. Together they count and measure where either alone would struggle.

Can it count product floating in water?

Yes. LiDAR and AI vision are trained to separate product from water, splash and foam, so product in flumes and wash tanks can be counted and its load estimated.

Conditions

Does steam or vapor stop the system?

No, with the right placement. Sensors are positioned out of the plume where possible, protected with purge air, and readings are filtered for vapor.

What about dust from flour, sugar or spices?

Dusty lines use purge collars, sealed enclosures and a cleaning schedule so sensor windows stay clear.

Can the sensors be washed down?

Yes, where required. Sensors are installed in sealed enclosures rated for wash-down and mounted with stainless hardware.

Integration

Can results go to our PLC or SCADA?

Yes. Counts, rates, volumes and levels can be sent over MODBUS, OPC UA or MQTT to your PLC, SCADA or MES.

How is accuracy checked?

Against your own references. At commissioning, counts and volumes are compared with manual counts or weighed batches, and the AI is retrained as products change.

Working with CRATUS

How do we get a proposal?

Send us the site layout, what you need to measure and how the space is used. A CRATUS engineer replies with questions, a sensor layout and a phased plan.

Can you work with our integrator, security or IT team?

Yes. CRATUS works directly with operations teams, system integrators and IT departments, and provides network requirements, installation instructions and remote support during commissioning.

Talk to a CRATUS engineer

Have a line that is hard to count?

Send us photos or a short video of the line and what you need to measure. A CRATUS engineer will reply with a sensor plan.

GET IN TOUCH

One of our experts will be communicating with you shortly. We are committed to understanding your application and providing support, tailored to your specific requirements.