The Quick Guide to Video Analytics: What You Need To Know

What is Video Analytics Software?

Video analytics software is a technology tool that automatically parses videos by applying artificial intelligence (AI), machine learning, and sophisticated algorithms. In contrast to traditional surveillance, which includes human operators monitoring video streams, video analytics software can detect, recognize and categorise things, individuals and behaviours on the spot. Suppose you have a packed shopping mall where the security guards find it impossible to follow every person’s movements. In the case of video analytics software, the system will also report unauthorised activity, such as dallying or gaining access to areas that aren’t in use. The proactive feature prevents security personnel from becoming stranded and delivers a massive increase in safety and operational efficiency. It’s the technology that lets enterprises and security networks get useful information out of a video stream or snapshot. Automated video analysis will make organizations much easier to manage, more efficient and more secure.

Video Analytics Software Key Advantages:

• Real-Time Detection: Instantly detect any anomalous behaviors, suspicious activity or anomalies in real-time video recordings. It can distinguish normal from abnormal activity and deliver more immediate response time and early detection. Moreover, real-time detection allows security teams to immediately respond to attack – reducing overall response times and reducing risk.
• Object Recognition: Recognize and classify objects (cars, human beings, animals). This feature helps to search and find specific objects efficiently within hours of recorded video. Intelligent object recognition — thanks to powerful AI — can even distinguish between objects that are identical, and be much more accurate in detecting potential security threats.
• Facial Recognition: Recognize faces for enhanced security in sensitive locations. Face Recognition can automate access management, track theft, and deter recurring crimes in a shopping or security environment. This allows for easy integration with access control solutions, offering enhanced protection to critical areas.
• Motion Detection: Record movement in restricted areas, providing notifications if movement is found in closed areas. This will allow for fast intrusion detection and real-time notifications to the security team. Today’s systems can vary sensitivity and introduce “safe zones” to minimize false positives and increase detection rates.
• Counting and Tracking: Count persons, vehicles, or objects and trace the movements of individuals on video frames. This is critical for crowd management, data analysis on traffic, and optimization of shop fronts. Businesses can use this information to optimize store layouts, congestion, and customer experiences.

Types of Video Analytics

There are various kinds of video analytics depending on the usage for which they are used. Each video analytics type has different strengths to cater different industries and purposes.

• Behavioural Analysis: This is a type that detects unusual or threatening behaviors, like squatting, making unexpected movements, or breaking in. This is particularly useful for sensitive areas such as airports, banks, and industrial facilities.
• Object Detection and Classification: Identifies and categorizes vehicles, humans, and other animals in the video stream. This feature allows companies to detect events like a vehicle crossing a security barrier.
• Face Recognition: Recalls and confirms the presence of people by scanning faces. It’s used in door locks, ticketing, and identification in crowds.
• People Counting: Marks the number of people coming and going in or out of a room. This information can be used to track foot traffic, store layouts, and compliance with occupancy restrictions.
• License Plate Recognition (LPR): Detects and records vehicle license plates. Parking management, Toll-booths and gated community access control applications are all made using this technology.
• Heat Mapping: Measures movement patterns in a place, helping businesses identify where people are going to be moving most often and map out the layout to improve the customer experience.
• Event Management: Keeps track of crowd size and movement in crowds to avoid jams and ensure event safety.

Technological Components of Video Analytics

Video analytics use a mix of cutting edge technology to provide precise real-time insights. Below are the essential parts driving video analytics platforms such as Eye Watch AI:

• Artificial Intelligence (AI) & Machine Learning (ML): AI algorithms pick up pattern and anomalies in the video feed. Machine learning models will “learn” from new information and get better with each subsequent update.
• Deep Learning: Deep learning models can use neural networks to crunch large amounts of video content and distinguish the smallest of objects, people, and behaviors.
• Edge Computing: Edge appliances crunch video data on-site, which cuts down on latency and delivers fast real-time processing. This lightens the load on cloud servers and enables faster detection and response.
• Cloud Computing: Cloud video analytics solutions let enterprises analyze video footage from a distance and store huge amount of video data safely. The cloud platforms also come with multi-site capabilities.
• Sensors & IoT: Motion sensors and IoT-connected devices provide extra data to video analytics tools, resulting in better detection and multi-layer analysis.
• GPU Acceleration: GPUs scale high-resolution video data and enable systems to process video data at higher speed and accuracy

To know more about AI analytics for surveillance, check out this article on AI Analytics for Surveillance.

Challenges in Video Analytics Implementation

The power of video analytics can be enlightening but there are certain hurdles you’ll have to overcome when implementing it. Below are some of the most common problems and how Eye Watch AI tackles them:

• Data Privacy Compliance: Privacy policies such as GDPR or HIPAA require businesses to safeguard users’ data. Eye Watch AI provides total encryption and monitored access to video footage, enabling organizations to remain compliant.
• False Positives & Alerts: Overwhelming security teams with unnecessary alerts. — Eye Watch AI’s programmable alert mechanism allows for customizable triggers, eliminating false positives and reporting incident information.
• Scalability: In companies with a growing presence, video analytics can be difficult to scale. Eye Watch AI is cloud-based, which makes adding cameras and storage a snap.
• System Integration: Analytics software can be difficult to integrate with legacy cameras and devices. Eye Watch AI allows for seamless connection to legacy hardware, so upgrading is easy and affordable.
• Low Latency: Real time monitoring requires low latency. Edge computing on Eye Watch AI reduces latency so that notifications arrive in real-time.

 

How to Choose the Best Video Analytics Platform?

The choice of the video analytics platform should be carefully considered. This is how you can take it step by step and determine the solution for your business:

1. Specify Business Use Cases: Figure out what your core use cases are, like People Counting, Face recognition, Object Recognition, etc.
2. Check Integration Ability: Determine whether the platform can be connected to your existing cameras, sensors, and video management systems.
3. Prioritize Real-Time Features: Real-time monitoring is crucial in security applications. Pick a platform like Eye Watch AI with real time notifications and processing speed.
4. Data Security: Look for platforms that are end-to-end encrypted, role-based access control, and data privacy compliant.
5. Search for Customization: Custom alerts and dashboards allow businesses to customise the system.
6. Evaluate Cloud vs. Edge: You can opt for cloud or edge analytics, depending on your latency, storage, and security requirements

Why Choose Eye Watch AI?

Eye Watch AI features powerful AI video analytics, robust security and intuitive operation. Here’s why Eye Watch AI should be your number one option:

• Deep Analytics: Behaviour analytics to facial recognition, Eye Watch AI supports every major use case.
• In-Depth Monitoring: Receive real-time notification of suspicious activity, so as to respond more quickly.
• Data Privacy: Keep yourself compliant to privacy laws such as GDPR with Eye Watch AI’s complete encryption and granular control.
• Custom Alerts & Dashboards: Create customized alerts and reports to suit security needs.
• Edge & Cloud Access: Get edge computing for real-time processing and cloud storage for scaling.

 

Pricing and Return on Investment of Video Analytics Solutions

Video analytics can yield a lot of dividends. Following are some of the ROI driving factors:

• Cost Effective: Automation reduces the manual surveillance, saving on the costs of human labour.
• Stock Shutdown: Thefts are caught on time using tools such as Eye Watch AI, reducing stock loss.
• Customer Experience: Heat mapping and people count make store layouts optimized, which improves sales.

Case Studies and Success Stories

Case Study 1:

Retail Store Theft Prevention A retail chain implemented Eye Watch AI’s video analytics to identify suspicious behavior in stores. By using behavioral analysis and real-time alerts, store managers were able to prevent theft, reducing shrinkage by 30% within six months.

Case Study 2: Smart City Traffic Control An intelligent city project used Eye Watch AI’s license plate scanning and object recognition to prevent traffic jams. The system automatically flagged vehicles involved in traffic accidents and decreased congestion by 25%. Case Study 3: Hospital Patient Tracking With Eye Watch AI, patients were tracked using the facial recognition and heat mapping functions of a healthcare facility. This helped staff to identify patients with dementia and reduced patient wandering incidents by 40% within six months.  

Glossary of Key Terms

• Edge Computing: Local processing of data on devices to minimize latency.
• Heat Mapping: Map of hotspots in a place.
• License Plate Recognition (LPR):  Automatic identification and recognition of vehicle plates.

  If you’re ready to take your surveillance business to the next level, then come and join the AI video analytics revolution. With Eye Watch AI, you have video analysis, real-time monitoring, and proactive security alerts that are the best on the market, Contact Eye Watch AI for a free demo.