While Comtex has witnessed firsthand the transition from traditional systems to AI
powered security camera and CCTV solutions, understanding the differences between
the two can provide valuable insights.
Traditional IP System: Reactive because it requires human monitoring and the review
of recorded footage after an incident.
AI Camera system: Proactive because the AI has advanced software algorithms that
analyze footage in real time, identifying and instantly responding to potential threats by
generating alerts of suspicious activities.
Traditional IP System: Reliance on manual monitoring is prone to human error. Long
shifts, fatigue and oversight can cause security staff to miss incidents.
AI Camera System: Consistently scan footage 24/7 without getting tired. It can identify
unusual patterns or potential threats, providing a level of constant vigilance that human
employees cannot match.
Data Management & Storage:
Traditional IP System: Not time efficient because it requires a human to sift through
hours of recordings. Storage typically relies on local hard drives, limiting the amount of
footage stored. Sometimes slow retrieval of specific events.
AI Security System: Cloud storage and AI tagging have made it much easier for
businesses to store, retrieve, and review security footage. By intelligently categorizing
recordings, AI allows users to quickly find specific events without manually sifting
through hours of video. This not only makes storing large amounts of recorded footage
more manageable but also significantly speeds up the review process.
Efficiency & Scalability:
Traditional IP System: Requires constant monitoring by security staff, increasing
operational expenses. Expansion often means increasing costs because you need more
people to monitor the additional cameras.
AI Security System: Monitoring tasks are automated, reducing the need for staff
oversight and lowering operational expenses. AI can simultaneously handle multiple
feeds which allow additional cameras to be added without a proportional increase in
monitoring staff.
Traditional IP System: Relies heavily on the experience and expertise of the operator
to differentiate between a threat and innocent activities. The effectiveness can vary
depending on the individual’s alertness and judgment.
AI Security System: AI systems maintain a consistent level of higher accuracy,
reducing human errors and biases. They objectively analyze footage based on
algorithms.
Flexibility & Integration:
Traditional IP System: Earlier systems had limitations when it came to integrating with
newer technologies or devices.
AI Security System: Modern AI solutions are designed with integration in mind. They
often work seamlessly with other IoT devices and technological platforms.
Traditional IP System: Slower response time. The speed of response depends on
human reaction times and manually sifting through recordings. Delays can sometimes
occur if an incident goes unnoticed.
AI Security System: Real-time alerts enable immediate response to potential threats.
AI systems can trigger automated alerts the moment they detect anomalies, potentially
reducing response times during critical situations.
Traditional IP System: Lower initial costs. Continuous costs from maintenance and
manpower is a concern for organizations, especially when considering expanding the
system.
AI Security System: Although there is a potentially higher initial setup cost, over time,
businesses can see savings due to reduced manual monitoring needs and streamlined
maintenance.
Traditional IP System: Generally, little privacy concerns because there is limited data
analysis. Continuous recording sometimes raises concerns about privacy, especially in
areas where individuals felt constantly watched.
AI Security System: The extensive monitoring and data collection can cause a higher
invasion of privacy. AI cameras do not just record video; they analyze, interpret, and
often store vast amounts of data about people and their behavior. However, AI systems,
with features like facial blurring or selective recording, can help address some of these
privacy concerns while still maintaining security.
It is possible that AI algorithms may make biased decisions without intending to lead to
discriminatory outcomes. To reduce these risks, there should be continuous evaluation
and updates.