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Real-Time Video Monitoring: The New Era of Remote Video Surveillance

Author
Ivan Muts
Published
September 18, 2023
Time
10 mins to read

Table of Contents

    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:

    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

    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:

    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.

    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:

    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?

    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.

    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:

    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:

    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 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.

    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:

    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.

    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.

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