Let’s imagine such an incident: a bomb exploded in the shopping mall. How would one identify the perpetrators, or even better how to prevent such a situation from happening? Let’s say there are an incredible amount of cameras installed at each corner of the building and they are operating throughout the day. But what value do these cameras bring to security measures? Even if a couple of operators are sitting in their control room watching 8 hours per day, there are no guarantees that a possible incident can be discovered at the moment of its occurrence. Therefore, many incidents are discovered only after being reported, and it can take days and days to check all the camera surveillance data to catch a villain.
In such a scenario, a real-time video content analysis (VCA) may be dramatically helpful. It can help handle various social, political, security, manufacturing, and many more other issues by performing real-time monitoring of events and using multifaceted algorithms to identify the problem.
The video surveillance market aka CCTV (closed-circuit television) is expected to grow up to $18,890 mln by the end of 2027. The insights that can be derived from the data processed from the video are immense and impactful in their possibilities to enhance business intelligence. Backed by AI, real-time video monitoring has become sophisticated enough to recognize unpredictable and unconventional patterns from massive data amounts. This is a tremendous solution for businesses trying to improve their operations from different perspectives.
A short explanation of how video monitoring works is in the video below:
What is real-time video surveillance and how does it work?
Real-time video surveillance goes far beyond installing video surveillance cameras: it is a cutting-edge technology that includes video content analytics (VCA) and can automatically analyze video content, detect objects and events based on predefined algorithms. Considering that video cameras generate endless quantities of footage, it is impossible for security staff or operators to permanently view each camera and detect suspicious behavior. Therefore, most often incidents are investigated once they are detected. It is time-consuming, tedious, and doesn’t provide data-driven results.
To enhance traditional remote video surveillance utility, real-time video monitoring technology, objects and people tracking technologies, and asset tracking solutions come into play to easily and quickly identify items and analyze them in mere minutes. Based on object attributes, movement and behavior, face recognition patterns, suspicious persons, the sudden burst of flames, or any other signs can be detected. Therefore, real-time monitoring can deter criminal activities before they occur.
Smart video analysis technology helps improve situational awareness through customized real-time alerts. They are triggered once the unusual activity is identified. Based on specific pre-defined criteria, video surveillance operators set up alerts.
Video surveillance alert criteria

The software criteria for video analytics include:
- Object appearance similarity. Based on these criteria, alerts are triggered, for example, when there are objects (bikes, cars, etc.) or persons who are not supposed to be in a certain location, or when someone is dwelling in the area. Alerts can be triggered even based on color clothing criteria. For instance, if there is a closed area only for private employees in uniforms, other persons wearing clothing of different colors will be tracked and notified as suspicious ones. With this functionality, if more people than expected are dwelling or loitering, for example, near the store inventory, the camera will trigger alerts to make security staff respond quickly.
- Count-based alerts. Alerts that are based on the count of the number of objects in certain areas can help control traffic or crowd. For example, if long queues are detected in the store or the airport check-ins, managers can quickly address this issue thanks to real-time video monitoring. Moreover, with occupancy detection functionality, lights can be switched off if there is no one in the room.
- Face-recognition alert. Based on digital images extracted from video records, security staff can easily pinpoint suspects in real time.
Euristiq approach
Real-time video analytics for intelligent video surveillance
Let’s look at the case where our client, an insurance company, faced the need to collect more data on drivers’ behavior and explore the environment in which accidents happen. The task of the software team was to develop a cloud-based IoT solution that would optimize vehicle insurance policies. The project discovery phase showed more prospects for the client. With the data collected, the client could not only see the accidents or their precursors but also implement preventive measures.
Technical architecture

Components of the solution
1. Road unit
A dash camera is cut both ways – road and driver facing. It is connected to the power supply of the vehicle and car accessories to get information about the car. Mounted near the rearview mirror, it enables a good overview of the road and the driver. Along with the cameras go a microphone, speaker, and a micro SD slot.
2. Cloud Center
As a means of connection between the cloud and the camera, an LTE module was used. It sends the following information about the vehicle:
- Location
- Speed
- Altitude
- The direction of movement (displayed on the map in degrees)
- Alerts detected by the camera (speeding, collision warning, etc.)
The operator can request a camera to upload a video of a particular incident by selecting the time and date.
The cloud control center holds information on the driver and movement of the vehicle and recording. With the camera capabilities, potential incidents are not just documented but could be prevented. Anytime a precursor of an incident is detected, the device installed in the vehicle sends an alert to a monitoring user. A monitoring user is a person responsible for checking the video sent from the cloud and activating the alert for the driver.
3. Connectivity modules
To enable communication of the camera with the cloud, WiFi, GPS, and Bluetooth connectivity modules were selected.
- WiFi module
- GPS module
- Bluetooth
4. Sensors
G-sensor and parking monitor. Since the cameras have to detect potentially dangerous situations, they need sensors to track the sudden change of direction resulting from emergency braking, clash, etc. For monitoring driver’s behavior, G-sensor and parking monitor were selected as priority ones.
5. Visualization of analytics
The effectiveness of hardware used for video monitoring is enhanced by the software developed in accordance with the client’s needs and requirements. In the given case, the collected data served multiple purposes. There were three types of users who had access to it:
- Monitoring center operator
- Fleet owners
- Clients admins
For the convenience of use, all the stakeholders were provided with interactive dashboards representing statistics of every driver, categorized videos, and a map.
What was achieved?
The client’s challenge was in monitoring the driver’s behavior and identifying the risks on the road. Such data directly influenced the financial outcomes for the insurance company. With the platform for real-time video monitoring and analytics, the client can easily minimize unreasonable expenses. In addition, driver’s coaching can be introduced and enhanced as a preventive measure. The scalability of the software allows the client to get more out of the telematics and analytics, and the process of its improvement is ongoing.
5G and AI: The new era of remote video monitoring?
Remote video monitoring with 5G
Although 4G networks have already successfully covered the majority of custom IoT software solutions, the excitement towards using 5G in real-time remote video surveillance didn’t abate.
A drastic decrease in latency from the current 50-100 milliseconds in 4G networks to 1-4 milliseconds in 5G, is projected to be game-changing for camera responsiveness and real-time video monitoring. One more important advantage of 5G connectivity is a jump in security camera image quality towards supporting 4K and 8K videos. This will ensure smooth and instantaneous live video footage, giving security personnel the ability to faster identify perpetrators and/or react to incidents and emergencies.
Another benefit that 5G has to offer to video surveillance is vast connectivity in cities or other congested spaces where multiple users are trying to connect simultaneously. This causes lags that are unforgivable in mitigating risks. With 5G this problem is resolved as this network provides connectivity at a faster and uninterrupted speed for more devices. To compare the capacity, the 4G can accommodate 1 million devices over 500 square kilometers, and 5G will fit the same number of devices on the same network over 1 square kilometer.
With its high speed, ultra-low latency, secure connectivity, and enhanced capabilities for mobile streaming of surveillance footage, 5G technology will open new possibilities for remote video monitoring. For more information about IoT networks read this guide.
Real-time video monitoring with AI
In contrast to traditional video management systems (VMS) that are cloud-based video surveillance solutions, AI-powered video content analysis technology has made a huge leap forward thanks to the use of Deep Neural Networks (DNNs). With the development of Deep Learning, identifying specific objects and recognition of particular patterns have become easier than ever.
AI-backed video surveillance systems work on the basis of specific algorithms allowing to provide real-time analysis of data to transform it into intelligent and actionable insights. These insights are further aggregated to present historical charts, graphs, heatmaps. The main point of this is that all the processes and analyses are performed without human intervention.
How does AI-based real-time monitoring work?
- Initial research of the issues is performed from multiple perspectives to define potential technological approaches.
- Based on the research, tech engineers create and test Machine Learning algorithms to identify people and objects within video frames.
- AI system is trained to recognize specific patterns.
- The system is deployed.

Safer Driving with Road Traffic Monitoring

Telematics Fleet Management Software

Advanced Foot Traffic Analytics
Benefits of real-time video surveillance system
Nowadays, video content analytics technology is evolving, and to increase ROI, streamline security systems, and enhance customer experiences, businesses have to upgrade the utility of video surveillance camera networks and maximize the value of existing infrastructures. Real-time alerts triggered by advanced video content analysis software help improve situational awareness and accelerate measures toward security, emergency responses, detection of unusual activities, better understanding of customer needs, and much more. Let’s categorize the main benefits of VCA systems so that you can weigh the pros and cons to understand if your business really needs this innovative approach.
- High-level protection. This benefit relates not only to public safety but also monitoring of high-risk areas. The real-time streaming of video helps detect loitering, identify suspicious objects that can affect your organization, or ensure timely safety in accident-prone areas. Moreover, if your facility contains dangerous chemicals, for example, real-time video monitoring helps remove the risk of people being located nearby. In contrast to conventional approaches toward video surveillance, live video monitoring backed by artificial intelligence algorithms is capable to track and detect each object that appears. With advanced video analytics, you are able to create a structured database of insights retrieved from raw video data resulting in smart alerting, granular search, and actionable reporting. While usual video cameras cannot grasp the entire view of moving objects due to color restrictions, long distances, weather conditions, video content analysis, based on neural networks that are trained to recognize different patterns from massive data, ensures high detection accuracy and reliability.
- Predictive maintenance. Combined with AI and IoT systems, video monitoring systems can anticipate problems before they occur. Aggregating large data amounts into comprehensive insights, live video monitoring powered with AI and IoT sensors facilitates preventative security strategies. Therefore, rapid search capabilities are applied to trigger alert notifications in real-time so that security staff can be timely informed of any alarming situation. And here we don’t mean intelligent image processing, but the integration of video analysis with other systems such as access control, time tracking, etc. AI-based patterns play an important role in the behavioral analysis as well.
- Sales and marketing capabilities. Going beyond the traditional paradigm of video security system that generates footage, real-time video monitoring systems allow for the enhancement of customer experiences. With that said, we mean retail businesses that can extremely benefit from advanced video technologies by amplifying their customers’ experiences. With insightful video analysis, you are able to retrieve meaningful heatmapping data such as the most occupied areas in the store, where your customers stop the most, and even where they are looking. There are a variety of advantages to drive your marketing decisions and increase your ROI. Read on to know more.
Remote video monitoring use cases
Real-time video monitoring for smart cities
There are a lot of areas in smart cities where real-time video monitoring can help improve efficiency, and effective management, and enhance preventative measures. Let’s see some of the examples:
- Smart surveillance systems monitor road networks and people moving across the city. With video analytics, such systems can not only identify road accidents but also alert ambulance or police workers immediately. Moreover, based on smart data analytics, roads can be closed and routes can be adjusted to prevent congestion issues. The intelligent road traffic monitoring system that is connected with camera sensors collects data. Such a monitoring system can automatically detect incidents based on obtained data from the sensors. One example is road traffic monitoring software that was implemented by Euristiq in the Dublin Port Tunnel. The system generates different types of alerts and insightful analytics in real-time on the map. With such video analytics, you can see the average speed and journey time of a vehicle of a certain day, the average waiting time in traffic jams, pedestrians movements, etc. Based on these reports, IoT systems generate appropriate alerts to immediately act on problems that enhance overall city prosperity.
- Real-time video monitoring incorporated with IoT empowers smart cities with effective parking management. Drivers can easily find available parking spaces through apps on their smartphones and unauthorized vehicles parked in pre-defined zones can be easily detected.
- The management of public venues can also be improved thanks to video analytics which detect queues at entry points. Remote video surveillance plays an important role in tackling of such issues and facilitates the regulation of people flows.
- From a sustainability perspective, smart real-time monitoring systems and video analytics can help city authorities reduce pollution, optimize energy consumption, and prevent climate crises. For example, video analytics and IoT-powered sensors can detect and flag potential water contamination, or improve traffic flow to protect citizens’ health. Smart city lighting solutions can extremely optimize energy consumption and reduce maintenance costs. Our team implemented a smart city lighting solution for Danish international company Novalume that resulted in reducing of maintenance costs and CO2 emissions up to 75%.
Components of road traffic live video monitoring system

Face recognition using remote monitoring
Being a biometric technology, face recognition can precisely identify people by analyzing their faces based on pre-defined patterns. A scanned image from a video is compared with images in the database and based on certain features it is matched up. Moreover, face recognition help recognize much more specific things about faces: gender, age, the direction of eyes, etc.
Besides public safety and security applications, where face recognition technology is mostly used for fighting crimes, it is also applied across other industries to fulfill specific tasks.
At airports, for example, face recognition can be used to verify travelers’ identities at customs. Biometric scanning systems, including facial identification, are predicted to be used widely due to the COVID-19 pandemic as touchless interactions. There are already such solutions available in U.S. airports where passengers can use facial scans from their check-ins to board a plane. Furthermore, facial recognition technology can be applied in airports to prevent terrorist attacks.
The hospitality industry is an area where face recognition can greatly make an impact on efficient customer service and robust security systems. Let’s outline the main use cases of facial identification in hotels:
- For security and access purposes, facial scans can be used to grant hotel guests access to their rooms and identify troublesome guests who have already been removed from the premises.
- Customers can authorize their payments by facial recognition without the need to interact with a single hotel employee.
- With real-time monitoring via face scans, hotel owners can research their guests and gather data on their expressions, facial features to identify age and gender, etc.
- Even before a customer’s check-in, facial recognition can help hotel employees deliver a greater level of customer support and more personalized greetings, for instance.
Medical institutions and hospitals can also benefit from face recognition. It relates to mental healthcare where video content analytics analyze facial features, expressions, body postures, and gaze to identify diseases. For example, the National Human Genome Research Institute uses facial recognition software to diagnose a rare genetic disease called DiGeorge syndrome that affects children in Africa, Asia, and Latin America.
Real-time video monitoring in smart farming
With digital camera monitoring systems, farmers can get real-time analytics and keep track of every operation in an effective and flexible manner. Farmers have already started to embrace IoT-powered technologies to make their agricultural processes more sophisticated, data-driven, and optimized. Backed by advanced analytics and remote monitoring systems, connected farming enhances farmers’ capacities. Let’s define the benefits farmers can gain:
- Real-time data collection through video cameras aids in tracking equipment efficiency.
- Real-time monitoring applications give more control in hands of farmers since they can detect malfunctions and correct them immediately. That, in turn, allows farmers to prevent shut-downs and large expenditures on asset repairing.
- Farmers can significantly save up time with permanent access to their IoT applications, and remote video surveillance contributes to secure farming management. There is no need to be involved in all the farming processes since remote monitoring helps ensure safety and comfort.
- Utilizing wireless technologies and video analytics, farmers are empowered to obtain precise analytics to adjust animals’ nutrition and overall healthcare and use smart spraying in agriculture to reduce water and pesticide use. Moreover, with video monitoring systems you are always aware of your cattle location.
Real-time video monitoring in smart retail
According to Oracle research, 66% of companies utilize IoT technologies to facilitate the customer experience. Machine learning algorithms and advanced video analytics have become breakthrough technological trends in the retail sector in recent years.
Determining your customers and identifying their preferences and behavioral models can significantly contribute to your overall marketing and sales strategy. Video analytics software helps generate actionable insights on customers’ characteristics, gender, age, and their walking patterns. You can even identify how much time your customer spent viewing a certain product by analyzing the direction of their gaze. All this information can impact your decision-making strategies so that you can maximize sales and improve customer experiences.
Retail video analytics solutions: improving store performance
Retail video analytics solutions provide valuable insights that help retailers optimize store layouts, improve customer experience, and drive higher sales. By leveraging AI-driven video analytics for retail, businesses can gain a deeper understanding of shopper behavior and store efficiency.
- Optimize store layouts. Test and refine floor plans to enhance customer flow and maximize engagement.
- Maximize high-traffic areas. Identify key zones within the store to reduce underutilized spaces and improve merchandising strategies.
- Measure design impact. Analyze how layout changes influence sales, dwell time, and shopper movement in different sections.
- Improve product placement. Strategically position products by category to create a seamless shopping experience and increase discoverability.
- Enhance store conditions. Detect lighting, temperature, or signage issues that may affect customer comfort and purchasing decisions.
- Improve security & loss prevention. Implement retail store video surveillance to monitor theft-prone areas and ensure customer safety.
- Enhance operational oversight. Use retail video monitoring to track employee efficiency, checkout line congestion, and store cleanliness in real time.
By implementing retail video analytics solutions, businesses can make data-driven improvements that boost efficiency, enhance customer satisfaction, and increase revenue.
Enhancing logistics security with real-time video monitoring
Logistics live video monitoring solutions provide real-time oversight, helping businesses prevent theft, track shipments, and optimize operations. By integrating logistics live security surveillance, companies can monitor warehouses, freight yards, and fleet movements, reducing risks and improving response times.
Modern logistics real-time video monitoring systems leverage AI-driven analytics, cloud storage, and IoT connectivity to provide instant alerts for suspicious activity, unauthorized access, or operational inefficiencies. These systems can integrate with access control, GPS tracking, and automated reporting tools, giving logistics managers a comprehensive view of their supply chain.
Investing in logistics video monitoring software enhances both security and operational efficiency. Features such as high-definition live streaming, remote access, and automated incident reporting enable businesses to make data-driven decisions, streamline workflows, and reduce losses. With real-time monitoring, logistics companies gain full visibility into their operations, ensuring compliance and improved customer satisfaction.
Here are the benefits of implementing logistics remote surveillance software:
- Identify retraining needs. By analyzing recorded footage through video analytics for logistics, managers can assess employee performance and identify areas for improvement.
- Respond to issues in real time. Logistics live monitoring ensures immediate alerts, allowing businesses to take swift action against theft, damage, or safety hazards.
- Virtual guarding. AI-powered logistics remote surveillance reduces reliance on physical security staff while maintaining constant monitoring.
- Remote monitoring. Businesses can access logistics remote video security feeds from anywhere, ensuring oversight of multiple locations without on-site presence.
- Better asset protection/loss prevention. Logistics remote surveillance helps prevent unauthorized access and theft by providing continuous monitoring of valuable assets.
- Reduced labor expenses and hiring needs. Automating security with logistics live monitoring reduces the need for additional security personnel, cutting costs.
- Better security with faster emergency response. Real-time video feeds help security teams and law enforcement respond quickly to security incidents.
- Alarm verification. Video analytics for logistics ensures that alarms are verified through recorded footage, preventing false alarms and unnecessary dispatches.
- Reduced inventory shrinkage. Logistics live monitoring deters theft and mismanagement, minimizing inventory loss across warehouses and distribution centers.
- Enhanced safety. Logistics remote surveillance monitors adherence to safety protocols, reducing workplace accidents and liability risks.
- Optimized operations. Logistics remote video security allows managers to track loading/unloading efficiency, truck movement, and warehouse workflows.
- Document events. Recorded footage from logistics live monitoring can be used for compliance audits, investigations, and resolving disputes.
- Upgrade your access control system. Integrating logistics remote surveillance with access control ensures only authorized personnel enter restricted areas.
- Lower insurance premiums. Enhanced security through video analytics for logistics demonstrates risk reduction, often leading to lower insurance costs.
- Keep shipping and receiving on time. Logistics live monitoring helps track vehicle arrivals and departures, ensuring smoother loading and unloading processes.
Industrial remote video monitoring
Industrial remote video monitoring software enhances security, safety, and operational efficiency in manufacturing and industrial facilities. Using manufacturing live security monitoring, businesses can track production lines, detect safety violations, and prevent unauthorized access. The system sends automated alerts in case of anomalies, enabling quick responses and minimizing risks.
Benefits of industrial remote video monitoring
- Real-time surveillance. Monitor production areas, warehouses, and equipment remotely.
- AI-powered anomaly detection. Identify unauthorized access, worker safety breaches, and equipment malfunctions.
- Reduced operational downtime. Detect and resolve inefficiencies before they escalate.
- Regulatory compliance. Ensure adherence to industry safety and security standards.
- Cost savings. Reduce manual security costs through automation and AI-driven monitoring.
Technologies used for industrial software for video monitoring with these technologies:
| Technology | Use Case | What It Does | Industry |
|---|---|---|---|
| Amazon Rekognition | Object detection, facial recognition | Identifies people, objects, and activities in video streams | Manufacturing, Security, Logistics |
| AWS Panorama | AI-powered edge computing for video analytics | Processes video analytics directly on local devices without cloud dependency | Manufacturing, Smart Cities, Industrial Automation |
| AWS IoT Core | Cloud-based IoT device integration | Connects IoT-enabled surveillance cameras to cloud systems | Industrial IoT, Manufacturing, Logistics |
| Amazon Kinesis Video Streams | Real-time video streaming and analysis | Captures, processes, and stores video data for real-time monitoring | Security, Manufacturing, Smart Warehousing |
| AWS Identity & Access Management (IAM) | Access control and security management | Manages and restricts user access to security systems | Security, Manufacturing, Industrial Facilities |
| AWS IoT TwinMaker | Creating digital twins for industrial monitoring | Creates a digital representation of industrial facilities for remote monitoring | Manufacturing, Industrial IoT, Smart Cities |
| AWS Lambda | Automated event-driven processes | Executes automated workflows triggered by video or security events | Industrial Automation, Security, Smart Logistics |
| Amazon SageMaker | Building and training custom AI models for industrial insights | Develops AI-driven predictive analytics for industrial video monitoring | Manufacturing, AI Development, Industrial IoT |
Computer vision in real-time video monitoring
While AI is at the center of discussions on automation and digital transformation, real-time video monitoring software has the potential to be revolutionized by computer vision. Businesses and security teams are increasingly adopting AI-powered tools, but many overlook how computer vision—a specialized field of AI—can dramatically enhance surveillance, operational monitoring, and security systems.
What is computer vision in real-time video monitoring?
Computer vision enables machines to interpret and analyze visual data from video feeds, identifying patterns, objects, and anomalies without human intervention. Unlike traditional surveillance that relies on manual observation or basic motion detection, computer vision-powered real-time monitoring can autonomously process vast amounts of video data, extract meaningful insights, and trigger automated responses.
AWS Computer vision services for your business
AWS offers several computer vision services that businesses can leverage for real-time video monitoring, AI-driven analytics, and automated image processing. Here are the key AWS services for computer vision:
| AWS Service | Application | Use Cases | Industries |
|---|---|---|---|
| Amazon Rekognition | AI-powered image and video analysis | Facial recognition, object detection, security monitoring, content moderation | Security, Retail, Healthcare, Social Media |
| AWS Panorama | On-premises computer vision for existing cameras | Automated surveillance, worker safety monitoring, vehicle tracking | Logistics, Manufacturing, Retail, Smart Cities |
| Amazon Lookout for Vision | AI-based defect detection | Quality control, anomaly detection, predictive maintenance in factories | Manufacturing, Industrial Automation, Quality Control |
| AWS DeepLens | AI-powered edge device for real-time analytics | Retail analytics, facial/object recognition, security monitoring | Retail, Security, Smart Cities, Transportation |
| Amazon SageMaker | Custom machine learning models for vision applications | Custom AI solutions for image classification, object detection, real-time video analytics | Technology, AI Development, Research, Automation |
| AWS IoT TwinMaker | Creating digital twins with real-time video and IoT data | Facility monitoring, logistics tracking, predictive maintenance with IoT integration | Logistics, Smart Cities, Industrial Automation, Infrastructure |
Components of the in-building video monitoring system

Remote video monitoring can be your win-win solution if you are looking for answers to these questions:
- Who your customers are?
- When do they visit your store?
- How do they behave?
- Where is the best place to put items?
- Etc.
With advancements in deep learning and predictive analytics, remote video surveillance has become a crucial driver to accelerate business performance. With the capability to provide granular data that can drive powerful decision-making and ensure a new level of security, real-time monitoring systems can detect anomalies, accurately identify persons and their behaviors, improve customer experiences, and, finally, increase your ROI.
How to Implement Real-Time Video Monitoring Software in Your Business Using Euristiq’s 4D Framework
Whether you’re looking to integrate real-time video monitoring software with your existing systems, enhance your current setup, or build a custom solution from scratch, a structured approach is essential for success. At Euristiq, we apply the 4D Framework—a strategic methodology that ensures seamless implementation by aligning technology with business goals. Here’s how this framework can be tailored to deploying a real-time video monitoring system:
DISCOVER: Analyze your business needs
- Assess existing surveillance systems and integration points.
- Identify key use cases: security, logistics tracking, compliance, or operations.
- Ensure regulatory compliance and data security.
DECIDE: Define priorities & choose the right approach
- Select a cloud-based, on-premise, or hybrid system.
- Choose security, AI, and integration features (e.g., AWS Panorama, Amazon Rekognition).
- Weigh cost vs. ROI for long-term scalability.
DESIGN: Develop the system architecture
- Plan hardware (cameras, sensors) and software (AI analytics, cloud storage).
- Ensure seamless integration with existing IT infrastructure.
- Implement security measures like encryption & access controls.
DELIVER: Deploy & optimize
- Start with a pilot launch, then scale.
- Automate alerts and use AI-driven analytics.
- Train teams and continuously improve system performance.
Need to build a tailored software solution?
If you are looking for a solution to provide your company with a holistic view of your business operations and raise your business to a new level – let us know. We will answer your questions as to what solution will work best for you and how we can cooperate to tailor it to your specific needs.
FAQ
What is real-time video surveillance?
Real-time video surveillance, aka CCTV (closed-circuit television), is a remote monitoring technology that uses surveillance video cameras to monitor and analyze live video streams mostly for security purposes, such as determining criminal activity, investigating crimes, and responding to incidents, threats, or suspicious activities as they happen.
What is real-time video monitoring?
Real-time video monitoring refers to the continuous and immediate observation and analysis of live video feeds in real-time. Real-time video monitoring enables security personnel or operators to actively and promptly observe and assess events, activities, or potential threats as they unfold. This form of monitoring allows for immediate response and intervention, maintaining security and safety.
What is active video monitoring?
Active video monitoring is a real-time observation and intelligent video analysis to detect and respond to events or incidents with alerts. The analysis involves the use of advanced technologies such as artificial intelligence and machine learning for preventative monitoring outside or indoors.
What is a video monitoring system?
A video monitoring system is a network of cameras, monitors/display units and recording devices that capture and monitor visual information in a designated area. It allows for real-time or recorded surveillance of activities, providing a means to monitor and protect people, property, or assets.
What is real-time video analytics?
Real-time video analytics is the process of analyzing video content in real-time to automatically extract meaningful information, identify objects, recognize patterns, and detect events or anomalies in the video stream. This enables prompt decision-making and instant response to events captured in the video.








