Image and video recognition

Image and video recognition – a new dimension of automation

Image and video recognition is a comprehensive AI/ML-class solution that enables automatic analysis of images and video recordings in industrial and research environments. We apply it where traditional monitoring and manual methods fall short, including aquaculture, railway logistics, and Industry 4.0.

Why does this solution matter?

AI-based image and video recognition systems enable continuous, automated analysis with high accuracy, eliminating the need for manual intervention. They process data in real time, significantly accelerating decision-making cycles and improving production management quality.

Traditional methods of collecting visual data — such as manual sampling or inspections — are time-consuming, imprecise, and prone to human error. They operate with delays and do not allow for timely responses to operational changes.

What problems does image and video recognition solve?

Time-consuming manual measurements

e.g. manual counting of organisms or inspecting thousands of video frames.

Challenging visual conditions

Variable lighting, high object density (e.g., >200 individuals per image), similarity in object and background colors, and industrial infrastructure that hinders traditional analysis.

Operational disturbances and organism stress

In aquaculture, for example, manually catching animals to measure biomass affects their welfare and can disrupt production.

Low accuracy and delayed information

Sample-based measurements or visual inspections often lead to delayed decisions based on incomplete data.

How does our technology solve this?

Automated image and video analysis – AI systems automatically analyze and classify images and video recordings, enabling uninterrupted process monitoring without the need for manual data processing.
High accuracy in challenging conditions – Our models — for example, the tested YOLOv5 detector — achieved a relative counting error of approximately 6% in industrial environments.
Lower stress and improved animal welfare – In aquaculture, we eliminate the need to capture shrimp for measurements, reducing their stress and risk of injury.
Reduced operational risk for infrastructure – In railway transport, the system detects sleeper damage at an early stage, enabling quick intervention and preventing major failures.
Solution scalability – We turn prototypes into production-ready systems applicable across facilities, farms, and industries.
Real-time response and better operational data – Continuous monitoring (e.g., image capture every minute) and data processing enable faster production and sales decisions.
Technology partnership and expert knowledge – We don’t just deliver a tool; we support you with integration, data analysis, model optimization, and application in your specific business context.

Image and video recognition implementation methodology

Together with the client’s team, we identify objectives, input data (images, video), operating conditions, KPIs, and infrastructure constraints.

We define the solution architecture, select AI/ML algorithms, and prepare the data, integration, and reporting plan.

We build and deploy the system: imaging devices, servers/computing infrastructure, AI models, user interface (e.g., web dashboard), and provide training for the client’s team.

We provide operational support, measure results, optimize the solution, and plan for scaling and development of additional variants.

Throughout the entire process, we act as a true partner — your team and our experts work together to ensure a smooth, predictable implementation and effective knowledge transfer.

What do you gain by working with us?

Faster production and operational decisions through automation – saving time and reducing delays.
Lower manual labor costs and reduced risk of measurement errors.
Better operational data: improved quality, accuracy, and availability of information.
Minimized impact on the environment, organisms, and infrastructure – less invasive methods, greater sustainability.
Scalability-ready – a solution designed to grow with your business and adapt to future challenges.

Which industries can benefit from our system?

Aquaculture and water farming technologies – monitoring shrimp, mussel, and salmon populations and biomass.

Rail transport and infrastructure – detecting damaged sleepers and enabling preventive maintenance.

Industry 4.0 / machine manufacturing – line monitoring, part defect detection, and visual analysis of assembly.

Logistics and warehousing – automated packaging inspection, pallet classification, and real-time monitoring.

Other industrial facilities – wherever image or video recognition is required in challenging conditions (e.g., lighting, object density, changing scenery).

Image and video recognition is your next step toward automating visual inspections, improving operational efficiency, and gaining better real-time data. We invite you to explore our case studies and get in touch — together, we can design a solution tailored to your unique context.

FAQ

Our solution is a system based on AI and machine learning algorithms that automatically analyzes images and video recordings in real time. It operates reliably even in challenging industrial environments where traditional visual inspection methods fail. The system recognizes objects, measures, classifies, and highlights abnormalities based on visual data.

By automating visual processes, companies gain faster access to precise operational data, enabling more accurate decisions and avoiding delays. We reduce the need for manual work, minimize measurement errors, and improve the quality of collected information. In aquaculture, we eliminate the need to extract organisms for measurement, improving their well-being and reducing losses. In logistics and industry, systems detect defects or issues in real time, preventing costly failures and increasing operational efficiency.

The implementation process is based on our design methodology, starting with identifying business goals, operational conditions, and the type of input data — images, recordings, or camera feeds. Next, we define the technical architecture, select AI/ML algorithms, and plan integration with the client’s systems. In the next phase, we deploy hardware and compute components, configure models, and launch the user interface. After implementation, we provide team training, long‑term support, performance optimization, and solution scaling.

Yes, our solution is fully scalable and configurable. We can tailor the system to different industries, environmental conditions, data sources, and image formats. The system works both in the cloud and locally (on‑premise) and can be integrated with existing data platforms, sensing devices, and the client’s network architecture. We select hardware and algorithms to perform effectively in the specific business context, taking lighting, background, object movement, and visual density into account.

Requirements depend on the deployment scale and the types of data analyzed. For most use cases, you need an image source (camera, photos, video recordings), a compute environment (local server or cloud), access to operational systems, and the ability to integrate via API or data interfaces. Our team conducts an infrastructure audit and selects technologies to ensure smooth operation in the client’s environment.

Data security and privacy are essential. The system processes only visual data from agreed sources and operates in a controlled environment — locally or in a secure cloud. We do not store materials outside the client’s infrastructure without consent. We implement the system in compliance with the organization’s security policies, including user authentication, authorization, and encrypted communication. Additionally, we assist the client’s team in preparing an environment that meets industry standards.

After deployment, we provide comprehensive technical and expert support. We monitor model effectiveness, optimize operational parameters, help develop the system further, and integrate additional data sources or new locations. Our team supports clients at every stage — from data analysis, through system maintenance, to developing new features and application variants. We also provide knowledge transfer, training, and operational documentation tailored to the client’s organization.

Companies that have implemented our image and video recognition solutions report significant increases in measurement accuracy, reduced analysis time, and improved operational decision quality. In aquaculture, biomass and population measurements are achieved with a few percent accuracy without disturbing the environment of aquatic organisms. In rail infrastructure, the system detects track defects at early stages, reducing the risk of failure. In industry and logistics, the solution automates visual inspections, enables faster response to issues, and boosts production efficiency and safety.

Our systems are used in industries where image and video analysis is difficult or impractical to perform manually at scale. In aquaculture, we use them to monitor biomass and aquatic organism counts. In rail transport, they help detect infrastructure damage. In Industry 4.0, they support quality control on production lines and assembly. In logistics, they enable automatic inspection of pallets, packages, and packaging. These systems are effective wherever variable lighting conditions, high object density, or fast workflows hinder traditional inspection methods.

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