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.

Video-based Road Traffic Monitoring System

Real-time video surveillance for road traffic management & automatic incident detection.

What is real-time video content analysis and how does it work?

Video content analytics (VCA) goes far beyond installing video surveillance cameras: it is a cutting-edge technology that can automatically analyze video content and detect objects and events based on pre-defined 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 were 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

Real-time video surveillance software 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 implement preventive measures.

Technical architecture

Euristiq Approach: Real-time video analytics. Technical architecture illustrated

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 surveillance

Remote video surveillance 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.

Benefits of video content analysis 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 to the 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 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 at. There are a variety of advantages to drive your marketing decisions and increase your ROI. Read on to know more.

Remote 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, 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 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 video monitoring system

Components of real time road video monitoring system, Euristiq

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 aid track equipment efficiency.
  • Real-time monitoring applications give more control in hands of farmers since they can detect malfunctions and correct them immediately. That’s, 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 health care, 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 customer and identifying their preferences and behavioral models can significantly contribute to your overall marketing and sales strategy. Video analytics software help 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.

Components of the in-building video monitoring system

Components of building video monitoring system, Euristiq

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.
Video Monitoring & Analytics Software Development

Build tailored real-time video monitoring solutions on time and on budget.

Need to build a tailored software solution?

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.

If you are looking for a solution to provide your company with a holistic view of your business operations and rise 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.

  • Author Ivan Muts
  • Published October 27, 2022
  • Category IoT
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Video-based road traffic monitoring system for Dublin Port tunnel
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