Cloud AI vs Built-in Camera AI for False Alarm Reduction

Tech
12 min read

Cloud AI vs Built-in Camera AI for False Alarm Reduction

Whether you are in the banking, manufacturing, or insurance business, you will need to use surveillance cameras to ensure the physical security of your business premises. However, these surveillance cameras may quickly become costly investments when they confuse real threats with non-threatening incidents and cause false security alarms.Therefore, you need security cameras that reduce false security alarms as much as possible. When it comes to the types of surveillance cameras you can place on your premises, the following two types are the most common.

CCTV cameras with built-in AI algorithms:

These CCTV cameras capture and record images and transfer this data to a local NVR. They also have built-in AI algorithms that set off alarms for specific instances. However, these algorithms often operate with low accuracy rates in detecting false alarms because of the cameras’ limited computing power.

Cloud-based AI Surveillance cameras:

These cameras are internet-connected and transmit data to the cloud where alarms can be stored and analyzed by using advanced AI algorithms.
When you implement such a surveillance system, you are able to collect and run advanced AI analytics on your video data to improve false alarm detection rates. Furthermore, you can eliminate the cost of on-premise video data storage and save your personnel from doing maintenance.

WHY CLOUD AI IS SUPERIOR?

When it comes to reducing false security alarms, Cloud AI surveillance is better than cameras with built-in algorithms in terms of three key metrics:

Accuracy at detecting and eliminating false alarms

Cloud AI is superior compared to cameras with built-in algorithms. The primary reason for this is the static nature of built-in algorithms. When cameras are produced at factories, the manufacturer installs the cameras with an AI algorithm, which is not updated unless new firmware is uploaded into the camera. Furthermore, built-in AI algorithms are usually designed to operate on specific hardware. Therefore, if there is a new and improved version of an AI algorithm, it might just not work on older cameras. Put simply, you will have to purchase and install a new camera if you want to get the benefits of the latest AI algorithms.
Additionally, unlike cloud-based AI algorithms, cameras with built-in AI cannot improve their accuracy rates over time. This is because these modern cameras do not possess the computational power needed to train an AI algorithm. Such resources are available only in the Cloud or big private data centers.

Customizing to business needs

Each business is unique in terms of its security needs and there is no one-size-fits-all solution. The nature of false alarms may change over time and may require businesses to install more cameras, reconfigure existing cameras or even change focus from one type of threat to another.
Thanks to Cloud-based AI, businesses can quickly adapt to ever-changing environments add or remove detection features, apply filtering logic, do business intelligence, and many more without investment into new equipment. Cameras with built-in algorithms, on the contrary, do not offer the same flexibility so more often than not businesses have to purchase, install and configure totally new cameras to get new features. 

Operational efficiency

Since Cloud-based AI surveillance has higher false alarm detection rates compared to cameras with built-in algorithms, it provides operational efficiency. Security personnel is exposed to fewer false alarms and this reduces the risk of false alarm fatigue. Cloud AI solutions are also highly scalable, allowing for the efficient processing of large amounts of video data from multiple cameras simultaneously. This scalability is particularly beneficial for large-scale deployments or organizations with numerous surveillance cameras spread across multiple locations.
Last but not least, Cloud AI facilitates centralized management and monitoring of the entire video surveillance infrastructure, enhancing operational efficiency by providing a unified interface for configuring and analyzing false alarm reduction settings across multiple cameras.

HOW TRACES AI CAN HELP? 

Traces FAF is a Cloud AI Based solution specifically designed for security companies and remote video monitoring centers. Our algorithms instantly eliminate up to 95% of all false alarms and provide deep insights about protected premises. We provide seamless integration with other systems and platforms, such as video management systems, and can work with any IP-based camera. 

Traces reports provide invaluable insights into the performance of your security cameras, allowing you to gain a comprehensive understanding of their operations. These reports highlight key metrics such as the frequency of false alarms and identifying cameras that require additional attention or optimization. Here are some of the most sought-after insights that our customers derive from these reports:

  1. False Alarm Analysis: Our reports reveal which cameras generate the highest number of false alarms, allowing you to identify and address potential issues or fine-tune their settings for improved accuracy.
  2. Alarm Source Identification: Traces reports help you determine which cameras are triggering the most security alarms caused by humans, vehicles, or animals. This information enables you to focus on specific areas or adjust camera positioning for better target detection.
  3. Daytime and Nighttime Alarm Classification: By categorizing security alarms based on daytime or nighttime filters, our reports provide a clear breakdown of incidents occurring during different periods. This insight aids in understanding the patterns and adjusting surveillance strategies accordingly.
  4. Vehicle Activity Analysis: Traces reports can identify the types of vehicles entering your premises at specific times of the day. This information is valuable for monitoring traffic patterns, detecting unauthorized access, or optimizing security measures.
Traces AI FAF reporting

By leveraging these detailed reports, you can make data-driven decisions to optimize your security camera system, mitigate false alarms, enhance detection accuracy, and improve overall surveillance efficiency. Traces empowers you with actionable insights to ensure that your security operations are efficient and effective.

API Access

Traces offers comprehensive API access, empowering you with sub-second latency and a robust suite of advanced algorithms. By harnessing the power of our API, you can develop custom applications that precisely cater to your business's unique requirements and customer preferences. These applications have the potential to deliver personalized experiences, significantly enhance convenience, and facilitate the creation of innovative value-added services, allowing you to stand out in the market and differentiate your brand.

Detecting anomalies early on

With Traces AI, you can receive instant notifications when anomalous events take place. For example, if there is an unusual surge in security alarms triggered by a particular camera or if there are unprecedented incidents like a vehicle trespassing into restricted areas, Traces AI can promptly flag these occurrences and alert you. We ensure that you stay informed about any unexpected or abnormal activities within your monitored environment.

Continuous Improvement

Each time Traces FAF processes an alarm, it learns and becomes smarter. This means that over time, you receive increasingly precise detection, improved efficiency, and cost savings.Traces utilizes advanced deep learning algorithms, to continuously analyze and understand alarm patterns. As the AI system ingests more data and encounters various alarm scenarios, it refines its algorithms, enhancing its ability to accurately identify true alarms while reducing false positives for every individual customer. The new and improved AI is seamlessly deployed with zero downtime, ensuring the continuous operation of your surveillance system. The updates are automatically applied to the cameras that can benefit the most from the enhancements, eliminating the need for manual intervention from your in-house team. This streamlined process removes any hassle or disruption, allowing your team to focus on their core responsibilities without worrying about managing AI updates.

Traces AI FAF Continuous Improvement

Furthermore, the learning process of Traces AI is ongoing and dynamic. The system continues to adapt and improve based on real-world feedback and new data, ensuring that it stays up-to-date with evolving security challenges and maintains its high performance over time.

Advanced detection feature

Unlike conventional alarm filtering services, Traces goes beyond simply filtering out common nuisances like mosquitoes and spider's web. Our advanced system provides comprehensive insights into various objects captured by cameras, offering valuable business intelligence.
With the recent update to Traces API, you now have access to additional features, such as vehicle type and vehicle color detection for every alarm where a vehicle is detected. This information can be leveraged for a wide range of applications, including traffic analysis, parking management, or identifying specific vehicles of interest.

Traces AI FAF Advanced vehicle detection

Furthermore, Traces continuously enhances its detection capabilities, offering a multitude of other features including  Chat GPT integration. We will talk about this cutting-edge tech and what it can bring to your video security business in our upcoming articles, so stay tuned.

We understand that every organization has unique needs, so we encourage you to reach out to us and discuss your specific requirements. Our team will work closely with you to explore how Traces can provide tailored solutions to address your specific challenges and extract maximum value from your surveillance system.

Back to Recent News