2025 Industry Trends in IP Video Surveillance

By David Strickland, Vice President of Kenton Brothers

2025 Industry Trends in IP Video SurveillanceThe IP video surveillance industry has been evolving rapidly, driven by advancements in artificial intelligence (AI), cybersecurity, edge computing, and cloud storage. As security concerns continue to grow, organizations are investing in cutting-edge surveillance technology to enhance their capabilities. Among the top players in this space, Hanwha Vision (formerly Hanwha Techwin) and Axis Communications lead the camera market, while Genetec and Milestone dominate in video management software (VMS).

Let’s explore some key trends shaping the industry and how these technologies are driving innovation.

1. AI-Powered Video Analytics

AI-driven analytics have become a major focus in IP video surveillance. Both Hanwha and Axis cameras incorporate AI-powered object detection, facial recognition, and behavior analysis, reducing false alarms and increasing the accuracy of alerts. These capabilities allow security teams to proactively respond to incidents and optimize monitoring efficiency.

A key industry trend is the increasing use of deep learning algorithms to improve the accuracy of AI-powered analytics. Traditional motion detection often leads to excessive false alarms, especially in dynamic environments. However, deep learning models can differentiate between humans, vehicles, and other objects with much greater precision, reducing unnecessary alerts and improving security response times.

Additionally, AI-powered cameras are now capable of detecting anomalies such as loitering, abandoned objects, or unusual crowd formations. These advanced analytics help organizations prevent incidents before they occur, shifting the focus from reactive to proactive security management.

Genetec and Milestone’s VMS platforms leverage AI to enhance forensic search capabilities, enabling operators to filter recorded footage based on object attributes like clothing color, vehicle type, or license plates. This drastically reduces investigation time and increases operational efficiency.

2. Cybersecurity in Video Surveillance

As cyber threats escalate, the security of IP surveillance systems has become a top priority. Manufacturers like Hanwha and Axis implement strong encryption, secure booting, and firmware authenticity checks to prevent unauthorized access and hacking attempts.

One of the most significant industry trends is the adoption of Zero Trust security models. This approach ensures that no device or user is automatically trusted, requiring continuous authentication and monitoring to mitigate potential threats. IP video surveillance systems are now being designed with multi-factor authentication (MFA), role-based access control (RBAC), and end-to-end encryption to enhance security at every level.

Furthermore, regulatory compliance is playing a larger role in the industry. Organizations must adhere to frameworks such as GDPR, NIST, and CISA guidelines, which require comprehensive audit logs, automated patch management, and vulnerability assessments. Genetec and Milestone have integrated advanced cybersecurity features into their VMS platforms, allowing users to detect intrusions, monitor system integrity, and respond to cyber incidents in real-time.

Another growing concern is the rise of ransomware attacks targeting surveillance networks. To counteract this, manufacturers are embedding anomaly detection and AI-driven threat intelligence into their systems to identify and neutralize potential breaches before they cause significant damage.

3. The Shift to Edge Computing

Edge computing is revolutionizing how video data is processed. Instead of transmitting all footage to a central server, cameras with built-in processing capabilities analyze data on the edge, reducing bandwidth usage and improving response times.

Hanwha and Axis have introduced AI-enabled edge analytics that can perform real-time event detection and alert security personnel instantly. This reduces the need for constant human monitoring and enhances overall system efficiency. Milestone and Genetec’s platforms seamlessly integrate with edge analytics, allowing users to manage alerts and recorded data efficiently.

4. Cloud-Based Video Surveillance and Hybrid Storage

The demand for cloud-based video surveillance solutions is growing as organizations seek scalable, cost-effective storage options. While fully cloud-based systems are not yet the standard for enterprise security, hybrid models—where footage is stored both on-premises and in the cloud—are becoming increasingly popular.

Genetec and Milestone offer cloud-ready VMS solutions that provide flexibility in storage and disaster recovery. Hanwha and Axis cameras are designed to integrate with cloud platforms, ensuring that critical footage remains accessible even in case of on-premise failures.

5. Integration with Access Control and IoT Devices

Modern security ecosystems require seamless integration between video surveillance, access control, and IoT sensors. Genetec’s Security Center platform and Milestone’s XProtect VMS provide extensive support for third-party access control systems, allowing organizations to link surveillance footage with entry logs, biometric authentication, and other security events.

Hanwha and Axis cameras support open standards like ONVIF, making it easier for businesses to integrate their surveillance systems with a wide range of security technologies. These integrations enhance situational awareness and improve incident response times.

6. Advancements in 4K and Multi-Sensor Cameras

The demand for high-resolution video quality continues to rise. Hanwha and Axis are pushing the boundaries with 4K, multi-sensor, and panoramic cameras that provide superior image clarity and wide-area coverage. These advancements reduce the number of cameras required for large installations, lowering infrastructure costs while improving overall surveillance quality.

Transformation

The IP video surveillance industry is undergoing a significant transformation, with AI, cybersecurity, edge computing, and cloud integration shaping the future of security. Hanwha and Axis continue to innovate in camera technology, while Genetec and Milestone lead the way in VMS advancements. Organizations looking to enhance their security posture must consider these trends when upgrading their surveillance infrastructure to ensure they stay ahead in an ever-evolving threat landscape.

Does your company need help with all of this? We are here for you. Give us a call.

The Rise of AI in the Physical Security Industry

By David Strickland, Vice President of Kenton Brothers

The Rise of AI in the Physical Security IndustryAt Kenton Brothers Systems for Security, we are always focused on Innovation. We have a great saying: Innovate or Die

The physical security industry is undergoing a major transformation as artificial intelligence (AI) becomes an integral part of surveillance, access control, and threat detection systems. AI-driven security solutions are enhancing the effectiveness of security personnel, improving response times, and reducing operational costs. As organizations seek more proactive approaches to risk mitigation, investments in AI technology continue to surge across various sectors, including corporate enterprises, critical infrastructure, law enforcement, and public safety.

According to market research, the global AI spend in the security market is expected to reach $71 billion by 2027, growing at a CAGR of over 23%. Major players in the industry are investing billions in AI-powered surveillance, access control, and cybersecurity solutions, recognizing the immense potential of these technologies to reshape security operations.

AI-Powered Video Surveillance

AI is revolutionizing video surveillance by improving object recognition, behavior analysis, and real-time anomaly detection. Companies like Hanwha Vision and Axis Communications are embedding deep learning algorithms into their cameras, allowing for advanced analytics such as facial recognition, license plate recognition, and suspicious activity detection.

Traditional security systems often rely on motion detection, which can trigger numerous false alarms due to environmental factors like shifting shadows, animals, or weather conditions. AI-powered analytics refine this process by differentiating between routine activities and actual security threats. By leveraging neural networks and machine learning, AI can accurately identify threats such as unauthorized intrusions, abandoned objects, or aggressive behavior. As a result, security teams can prioritize real incidents and respond more efficiently, minimizing downtime and improving security operations.

Additionally, AI-enhanced surveillance systems can integrate with law enforcement databases, allowing for real-time identification of persons of interest, missing individuals, or stolen vehicles. This level of automation significantly enhances the ability to act quickly in high-risk scenarios.

Predictive Threat Detection and Incident Prevention

One of the biggest advantages of AI in security is its predictive capabilities. AI algorithms analyze vast amounts of historical data to identify patterns and predict potential security breaches. By integrating AI with physical security measures, organizations can take preventive action before incidents occur, reducing risks and enhancing preparedness.

For example, AI-driven behavior analytics can detect unusual activity in high-security areas, such as loitering near restricted zones or unauthorized access attempts. Advanced AI models can factor in variables like time of day, frequency of movement, and crowd density to determine whether an individual’s behavior is suspicious. Security systems can then issue alerts to personnel, allowing them to intervene before a breach happens.

AI-powered analytics can help in monitoring large-scale events such as concerts, sports games, and public gatherings, identifying crowd surges or potential stampedes in real-time. This proactive approach allows security teams to take action before incidents escalate into critical situations.

AI in Access Control Systems

The Rise of AI in the Physical Security IndustryAI is also reshaping access control by introducing biometric authentication, intelligent access policies, and adaptive security responses. Facial recognition, fingerprint scanning, and iris detection—powered by AI—are replacing traditional keycards and passwords, offering a more secure and frictionless experience for employees and visitors.

AI-driven access control systems can adapt to evolving security threats by learning user behaviors and flagging anomalies. If an employee suddenly tries to access a restricted area at an unusual time, the system can trigger additional authentication steps or alert security personnel. These AI-powered systems can also integrate with databases to enforce blacklists and whitelist protocols, enhancing perimeter security.

Additionally, AI-enhanced access control can be used in conjunction with workforce management, allowing for more efficient tracking of employee attendance, automated credential revocation for terminated employees, and secure remote access for approved personnel.

AI-Driven Robotics and Drones

The deployment of AI-powered security robots and drones is becoming more common in large-scale facilities, such as airports, warehouses, and corporate campuses. These autonomous systems can patrol designated areas, analyze footage in real-time, and even interact with potential threats using voice commands or alerts.

Security robots equipped with AI can identify suspicious behavior, recognize unauthorized personnel, and conduct temperature scans in high-risk areas. AI-driven drones, on the other hand, provide aerial surveillance, offering a broader perspective of security perimeters, which is particularly useful for securing large or remote locations where manual patrols are less effective.

Furthermore, these AI-powered security agents can work around the clock, reducing the need for human patrols while maintaining a consistent level of monitoring. Some of the latest models are equipped with environmental sensors that detect hazardous materials, making them valuable assets for critical infrastructure protection.

AI and Cybersecurity Convergence

As physical security systems become more connected, the risk of cyber threats increases. AI is playing a crucial role in bridging the gap between physical and cybersecurity by identifying vulnerabilities and mitigating risks in real time. AI-driven security platforms use behavior-based analytics to detect unauthorized access to surveillance networks, monitor unusual login attempts, and prevent data breaches.

AI-enhanced threat detection software can scan large amounts of data to recognize malware, ransomware, and phishing attempts, protecting security infrastructures from cyberattacks. By integrating AI with both cybersecurity and physical security systems, organizations can establish a more holistic security approach that safeguards against both digital and physical threats.

Security Information and Event Management (SIEM) platforms and Security Orchestration, Automation, and Response (SOAR) solutions are increasingly using AI to correlate events across different security layers. This ensures a more comprehensive security posture by automatically identifying, prioritizing, and responding to both cyber and physical security incidents in real time.

Future Outlook: The Growth of AI in Security

The integration of AI into the physical security industry is only expected to grow. Market analysts predict that investments in AI-driven security solutions will continue to rise as businesses, government agencies, and critical infrastructure providers seek more efficient ways to protect assets and people.

As AI technology evolves, new applications such as real-time audio threat detection, emotion recognition, and AI-enhanced forensic analysis will become more common. AI will also play a key role in autonomous security decision-making, reducing the reliance on human intervention and improving response times in emergency situations.

Future advancements in AI will also lead to more sophisticated autonomous security solutions, including AI-powered facial recognition gates for seamless access control, smart city surveillance integrations, and advanced threat prediction models that adapt in real time.

AI is Reshaping Physical Security

AI is reshaping the physical security landscape by providing smarter, faster, and more accurate security solutions. From advanced video analytics to predictive threat detection, biometric authentication, and AI-driven robotics, the industry is embracing a new era of security innovation. Organizations investing in AI-powered security solutions are not only improving their defenses but also setting the foundation for a future where security is more proactive, adaptive, and intelligent than ever before. The rapid evolution of AI in security is setting the stage for a safer world, where threats are detected before they occur, and response times are reduced to a matter of seconds.

Please give us a call to explore the ways AI can help your physical security systems, policies and procedures.

“Camera in a Box” Solution for Community Improvement Districts

By Neal Bellamy, IT Director at Kenton Brothers

"Camera in a Box" Solution for Community Improvement DistrictsThe use of cameras to help protect areas of the city has never been more prevalent than today. The increase in camera quality and capability has increased the effectiveness, while decreasing the number of cameras needed. License plate cameras have also never been more effective. City infrastructure has also given the city capability to transmit the video to central monitoring stations to assist with live issues. (Of course, any city’s funding will only go so far.)

Community Improvement Districts

Community Improvement Districts (CID) are groups of owners in an area that partner with their city government to help improve the economy, safety, beautification, and or capital improvements for its area. Here in Kansas City there are many established CIDs including Downtown and River Market, Crossroads, Main Street, 39th Street, Waldo, Troost, Truman Road and more.

Typically, these CIDs have a better understanding of their areas where safety and security needs are. However, CIDs typically do not have the resources to monitor or respond to their given areas through cameras in the area. This is where a partnership can help both a CID and the local police department.

Infrastructure? Check.

Many light poles have a plug on top to provide power. The network is available through either city infrastructure or 5G cellular connections. (5G is now fast enough to provide video feeds back to central monitoring.) Some cities even have their own local wireless network.

“Camera in a Box” from Kenton Brothers? Check.

"Camera in a Box" Solution for Community Improvement DistrictsThe CID can purchase a Swiss army knife type of solution that can be mounted permanently or temporarily as needed to provide coverage of specific areas. Many different types of cameras can be used such as license plate capture, PTZ, 360 degrees situational, Infrared, etc. Camera analytics have also improved greatly to help alert when specific license plates are found or when there is movement in areas that should not have activity.

The camera boxes that we are providing offer a lightweight, weatherproof (Nema 3R) pole or wall-mounted enclosure, 8 ports for cameras, up to 480 W of POE power, and a 5G/Wifi/Networked router with a plug to interface into the existing light poles. This will provide a solid base to which each location can be customized to the situation.

If a customizable Swiss-army cameras in a box type of solution help you or you local police department, let us know how we can help!

Radio Towers? Yes, We Do That

By Neal Bellamy, IT Director at Kenton Brothers

Radio Towers? Yes, we do that.In today’s episode of “Yes, we can do that”, I bring you Radio Towers. It’s not the first time we have placed equipment on towers, but this time I have pictures!

The Problem:

A municipality approached us with two issues they wanted to solve.

First, they wanted cameras installed in strategic spots around their city, but did not have any network infrastructure to get the signal back to the police station. Second, they wanted to create a security perimeter around the radio tower itself. There was some extra credit available if we could get some long-distance cameras mounted on the tower as well.

The Solution:

We wanted a high bandwidth link between the tower and the police station. We know that the city may add cameras later and the likely point of communication will go through the tower. Maximizing the link from the tower to the police station will future-proof the installation.

We chose Ubiquiti Air Fiber as that link. It is less likely to be affected by interference and provides a theoretical 1 Gigabit connection.

Radio Towers? Yes, we do that. Radio Towers? Yes, we do that. Radio Towers? Yes, we do that.

For the cameras in strategic locations, we wanted to provide flexibility in where the cameras and radios will be placed. We know that they will want to add cameras later and time will change the requirements for where the cameras are needed.

For these radios, we chose Ubiquiti AirMax Rocket Prism 5AC with a 120-degree sector antenna. The large angle allows the radio to be moved around as needed. Since we had two locations that were not within 120 degrees of each other, we needed two of these radios covering 240 degrees total.

The camera choice was simple: Axis Q6135-LE cameras fit the bill easily. With 32x optical zoom, the city will be able to see almost anywhere within several miles of the tower. These Pan-Tilt-Zoom cameras (PTZs) also have excellent low-light visibility. They wanted 360-degree coverage from the tower, so two cameras were needed.

To be clear, I don’t mind heights. But 175 feet in the air is above my limits and pay grade, so we hired a professional. Enter Kasper. Kasper’s Business Kaap Kom focuses on communication and radio towers. He came recommended to us by a current client. (After spending all day with him, I couldn’t recommend him enough.)

Radio Towers? Yes, we do that. Radio Towers? Yes, we do that. Radio Towers? Yes, we do that.

The Result:

Kasper did all of the scary work with us as his ground crew. It took seven hours to mount all the equipment, install the cables, and carefully align the radios. There were some hiccups along the way, but our team was able to get past each one and successfully deliver the desired result.

We ended up with over 750 Mbps link back to the police station and 350 Mbps for both remote links. The wireless connection can support around 100 cameras spread throughout the city wherever they are needed. The two PTZs can see details for miles. All in all, it was a mission accomplished and another great project. Radio Towers? Yes, we do that too.

Need help with your commercial security requirements? Just give us a call.

Radio Towers? Yes, we do that. Radio Towers? Yes, we do that. Radio Towers? Yes, we do that.

Facial Authentication vs. Facial Recognition: Understanding the Differences and Applications

By Gina Stuelke, CEO of Kenton Brothers

Facial Authentication vs. Facial RecognitionBiometric technologies have gained immense popularity for their convenience and enhanced security. Among these technologies, facial authentication and facial recognition stand out as two of the most discussed and applied innovations. While the terms are often used interchangeably, they refer to distinct processes and serve different purposes.

In this blog post, we’ll break down the differences between facial authentication and facial recognition, their underlying technology, and their real-world applications.

What is Facial Authentication?

Facial authentication is a biometric verification process where a system compares the face of a user to a pre-stored image (or template) to confirm their identity. This technology is primarily used in situations where a user must prove they are who they claim to be, such as when unlocking a smartphone, accessing a secure area, or logging into a banking app.

How it Works:

  1. Enrollment: The user enrolls their face into the system by scanning it, typically with a camera. This creates a template, which is a mathematical model of the facial features.
  2. Comparison: When the user attempts to access the system again, their face is scanned in real-time and compared to the stored template.
  3. Matching: If the live scan and stored template match within a certain threshold, the user is authenticated.

Key Features:

  • One-to-One Comparison: It compares a user’s face against their own stored template, confirming their identity.
  • Security: It is typically used in secure environments where users need to prove their identity (e.g., smartphones, banking apps).
  • User Control: Users usually initiate the process and consent to the comparison.
  • Common Applications:
    • Smartphone unlocking (e.g., Apple’s Face ID)
    • Secure access to apps and services (e.g., banking apps)
    • Physical security systems (e.g., building access)

What is Facial Recognition?

Facial recognition is a broader technology used to identify or verify a person from an image or video in a database or a public setting. Unlike facial authentication, facial recognition often works without the active involvement or consent of the individual and can be used in surveillance or identification tasks.

How it Works:

  1. Image Capture: A camera or video feed captures the face of a person in real-time or from a photograph.
  2. Feature Extraction: The system extracts facial features from the image and creates a biometric template.
  3. Database Search: The system compares the facial features to those in a large database to find a match.
  4. Identification or Verification: If a match is found, the person is identified or their identity is verified. If no match is found, they remain unidentified.

Key Features:

  • One-to-Many Comparison: Facial recognition systems compare a person’s face against many stored templates in a database.
  • Surveillance and Public Use: It’s often used in public spaces for surveillance, identifying individuals without their active participation.
  • Privacy Concerns: Since individuals may not know when their face is being scanned, the technology has raised privacy and ethical concerns.
  • Common Applications:
    • Law enforcement and criminal identification
    • Airport security and border control
    • Retail and commercial surveillance
    • Marketing and customer analytics (e.g., identifying returning customers)

Key Differences Between Facial Authentication and Facial Recognition

Facial Authentication

Purpose: To verify an individual’s identity
Comparison Type: One-to-one comparison (individual vs. stored template)
User involvement: Requires user participation
Security vs. Convenience: Primarily for security (e.g. unlocking devices)
Privacy concerns: Lower (user initiates the scam)
Common User Cases: Smartphone authentication, banking apps Law enforcement, public surveillance, marketing

Facial Recognition

Purpose: To identify or recognize individuals in a crowd
Comparison Type: One to many comparison (individual vs. database)
User involvement: Can be passive and without user consent
Security vs. Convenience: Primarily for identification tracking
Privacy concerns: Higher (can be used without user consent)
Common User Cases: Law enforcement, public surveillance, marketing

Privacy and Ethical Considerations

While both technologies offer undeniable benefits, they raise important privacy concerns, particularly facial recognition. Since facial recognition can be used without the knowledge or consent of the individual, it poses potential risks related to surveillance and the tracking of individuals in public spaces. Many governments and organizations are still working to strike a balance between the benefits of these technologies and the protection of individual privacy. On the other hand, facial authentication, which requires user consent and involvement, is generally considered less invasive, as it is used for secure access to personal devices or services.

Facial authentication and facial recognition are two powerful biometric technologies with distinct purposes and applications. Facial authentication is typically used to verify a user’s identity for security purposes, while facial recognition is used to identify individuals from a crowd or a database. Understanding these differences is crucial, especially as both technologies continue to evolve and become more integrated into our daily lives.

Whether you’re concerned about privacy, security, or convenience, it’s essential to stay informed about how these technologies are being used and regulated. We are here to guide you, give us a call.