Video analysis design
We define analysis units and result formats that fit the purpose, such as detection, classification, tracking, and zone analysis.
Video AI & data analytics
Drawing on our video processing and data analytics experience, we turn scenes and signals from the field into information you can analyze.
We turn raw camera and sensor data into information that services can use.
We have delivered video processing and data analytics projects, such as store video analysis and hazard prediction based on facility and sensor data. Building on this experience, we design data flows that fit the purpose of the analysis and the conditions on site. Rather than only showing model results, we set up collection, processing, review, and service integration as one process.
Feasibility and performance depend on camera conditions, data quality, and analysis criteria. We agree on goals and evaluation criteria through early validation on representative data.
When video and sensor data don’t lead to decisions
If this sounds familiar
When video piles up but isn’t put to use
We define the objects, states, and movements you need from each scene and structure them as data that services can use.
When camera setups and data vary by site
We check lighting, field of view, obstructions, mounting positions, and variation across samples, then set collection and evaluation conditions.
When results must feed existing systems
We deliver events, totals, and review images in the form that other systems, dashboards, and operations alerts need.
We build it with you, from analysis design to service integration.
Training & validation data
We collect representative scenes and exceptions, and document labeling criteria, quality checks, and how the data is split.
Model & pipeline implementation
We set up preprocessing, inference, post-processing, and result storage to fit site conditions and how processing runs.
Service screens & system integration
We connect analysis results to screens where staff can review them, and to existing systems and data storage.
We check site conditions first, then improve with operating data.
We define the site and the purpose
We first agree on the camera setup, the target scenes, the results you need, and how staff will use them.
We check with representative data
Using samples that cover both typical situations and difficult conditions, we look at what can be built and where the limits are.
We connect it to the service flow
We convert model results into events, statistics, and review items, and connect them to existing work screens.
We feed operating data back in
We review false positives and false negatives from the field, along with changes in conditions, to improve the data and processing criteria.
Project deliverables
- Definition of analysis targets and site conditions
- Data collection, labeling, and validation criteria
- Model PoC on representative data
- Result review screens and system integration
- Operational monitoring and improvement items
The exact scope and deliverables are confirmed in early discussions.
Related projects
Video analytics of store visitors and foot traffic
Capturing foot traffic outside a store and visitor flow inside it as data
- KPS’s role
- Using AI video processing to track and count passersby in real time, automatically recognize visitors and estimate their gender and age group, and turn visits into data by zone
- AI video processing
- Object tracking
- Gender & age group estimation
Fire prevention and hazard prediction AI for industrial facilities
Helping anticipate fires and hazardous situations at industrial facilities and respond to them
- KPS’s role
- Developing an AI facility management system for fire prevention and hazard prediction, and an equipment control (PLC) system
- AI risk prediction
- Equipment control (PLC)
- Facility management IoT
Common questions before a consultation
View all FAQsTell us about the site you want to analyze and the video and data you have.
Tell us about your current environment and the work you want to improve, and we’ll help define where to start.