“AI-powered detection” sounds impressive, but what does it actually mean? When we say GuardianAI detects humans with 98.7% accuracy, what’s happening behind the scenes?
This article explains the technology in plain language—no computer science degree required.
Traditional Motion Detection vs AI Detection
The Old Way: Detecting Change
Traditional motion detection works by comparing images. The system looks at Frame A, then Frame B, and asks: “Did anything change?”
If pixels have different values between frames, the system flags motion. Simple and effective for detecting that something moved.
The problem? It can’t tell you what moved. A person walking past looks like “pixels changed.” A cat walking past also looks like “pixels changed.” Wind blowing a tree branch? More changed pixels.
This is why traditional systems generate so many false alarms. They detect motion without understanding it.
The New Way: Understanding Images
AI detection takes a fundamentally different approach. Instead of asking “Did something change?”, it asks “What is in this image?”
When GuardianAI receives an image, it doesn’t compare it to the previous frame. It analyses the current image and identifies what it contains. Is there a human in this picture? Is there a vehicle? Or is it just animals, vegetation, and background?
This is the crucial difference: traditional systems detect change; AI systems recognise content.
How Does AI Recognise Humans?
Training the Neural Network
Before GuardianAI can identify humans, it needs to learn what humans look like. This happens through “training”—exposing the system to millions of images of humans in various situations:
- People standing, walking, running, crouching
- Humans from different angles—front, back, side, above
- Various lighting conditions—daylight, dusk, infrared
- Partial visibility—people partially behind objects
- Different sizes—close up and far away
- Various clothing and appearances
For each image, the system is told “this contains a human” or “this does not contain a human.” Over millions of examples, the neural network learns the patterns that distinguish humans from everything else.
The same process trains the system on vehicles, allowing it to distinguish cars and trucks from other objects.
What the System Learns
Through training, the AI learns to recognise:
Body proportions: Humans have specific height-to-width ratios, limb proportions, and body segment relationships that differ from animals.
Movement patterns: How humans walk, stand, and move differs from how animals move. Even in a single image, posture provides clues.
Shape characteristics: The outline of a human body has distinct properties—head shape, shoulder width relative to waist, presence of legs versus four-legged stance.
Contextual factors: A human-sized shape in a doorway is more likely to be a human than the same shape in a tree.
The neural network doesn’t follow explicit rules like “look for a round head on top of shoulders.” Instead, it develops complex internal representations that capture what makes something “human-like.” These representations are learned from data, not programmed by engineers.
The Detection Process
When your camera captures an image and sends it to GuardianAI, here’s what happens:
Step 1: Image Reception
The image arrives at GuardianAI’s cloud servers. This is a still photo captured by your camera when motion was detected—not continuous video streaming.
Step 2: Neural Network Analysis
The image passes through the neural network—a mathematical system with millions of internal parameters tuned during training. The network processes the image through multiple layers, each extracting different features:
- Early layers detect simple features like edges and contrasts
- Middle layers combine these into more complex patterns
- Later layers recognise high-level concepts like body parts and poses
- Final layers determine whether a human is present
Step 3: Detection Decision
The network produces a confidence score: “I am X% confident this image contains a human.”
If confidence exceeds the threshold, the detection is confirmed. The system also identifies where in the image the human is located, drawing a bounding box around the detected person.
Step 4: Alert Generation
If a human is detected:
- You receive an instant Telegram notification
- The notification includes the original photo
- A bounding box highlights where the human was detected
- Security services can receive the same alert
If no human is detected:
- No alert is generated
- You’re not disturbed
- The image may be logged for your records but doesn’t trigger notification
Total Time: 2-3 Seconds
From motion detection on your camera to alert on your phone typically takes 2-3 seconds. Fast enough for real-time response to genuine threats.
Why This Matters for Security
Eliminating False Alarms
Because AI actually identifies what’s in an image rather than just detecting movement, it can distinguish between:
- A person (alert) and a dog (no alert)
- An intruder (alert) and a shadow (no alert)
- A vehicle (alert if configured) and headlight glare (no alert)
- A human approaching (alert) and vegetation moving in wind (no alert)
GuardianAI eliminates 99% of false alarms because 99% of motion events aren’t actually threats. Only the remaining 1%—the actual humans—generate notifications.
Reliable Alerting
Because false alarms are eliminated, alerts become meaningful. When GuardianAI sends a notification, it warrants attention. This solves the “boy who cried wolf” problem that plagues traditional systems.
People don’t ignore GuardianAI alerts because they’ve learned the alerts mean something. This transforms security from noise (constant false alerts) to signal (verified threats).
Visual Verification
Every alert includes the photo that triggered it. You don’t just know that “the AI detected a human”—you can see the image and verify for yourself.
This enables informed response:
- Is this someone who should be there?
- How many people are present?
- What are they doing?
- Should I call armed response or just monitor?
Continuous Improvement
AI systems aren’t static. GuardianAI’s detection capability improves over time:
Expanded training data: As the system processes more images from real-world deployments, the training dataset grows.
Refined accuracy: Edge cases and difficult scenarios identified in operation inform system improvements.
Algorithm advances: Research in AI continues globally, and improvements can be incorporated into the system.
Because GuardianAI is cloud-based, these improvements deploy automatically. Your cameras keep sending images to the same servers, but those servers get smarter over time. No hardware upgrades or local software updates required.
Common Questions
“Can the AI be fooled?”
No security system is perfect. The AI can potentially be fooled by unusual scenarios it hasn’t encountered during training. However, at 98.7% accuracy, such scenarios are rare. Disguises, unusual postures, or partial visibility might occasionally cause missed detections or false triggers, but performance in typical security scenarios is highly reliable.
“Does weather affect accuracy?”
The AI handles various weather conditions well because it’s trained on images from different conditions. Heavy rain or fog might reduce image quality enough to affect detection, but this is a camera performance issue rather than an AI limitation. Infrared cameras maintain detection capability in complete darkness.
“What about privacy?”
Images are processed for detection purposes. GuardianAI analyses whether humans are present, not who those humans are—it’s detection, not facial recognition. However, as with any camera system, consideration of privacy regulations and ethical use is important.
The Bottom Line
AI detection represents a fundamental advancement over traditional motion detection. Instead of merely detecting that something moved, AI systems identify what’s actually in an image.
For security applications, this means the end of false alarms from animals, weather, and environmental factors. It means alerts that warrant attention because they represent verified human presence. And it means security systems that actually work as intended—protecting your property by detecting real threats and ignoring everything else.
The technology is sophisticated, but the outcome is simple: alerts when humans appear, silence when they don’t.
Experience AI detection yourself:
Contact GuardianAI at guardianai.co.za for a demonstration of our AI-powered surveillance technology.
GuardianAI uses advanced neural network technology to achieve 98.7% human detection accuracy. Our system processes images from existing CCTV cameras, transforming passive recording into active intelligent surveillance.