Thermal Imaging Night Vision Drone is a cutting-edge drone designed for all-weather monitoring and operations in complex environments. It is equipped with a highly sensitive thermal imaging sensor and a dual-spectrum night vision system. It can accurately capture the target's thermal radiation signals in completely dark, foggy or smoky environments, and generate high-contrast thermal images in real time. Its AI intelligent algorithm supports automatic tracking and classification of dynamic targets, and is suitable for scenarios such as security inspections, fire rescue, wildlife protection, and border patrols. Through multimodal data fusion technology, the device can simultaneously output visible light and thermal imaging images, and combined with a cloud data analysis platform, it provides users with multi-dimensional environmental perception and decision-making support. The fuselage adopts a lightweight carbon fiber structure, supports IP67 waterproof and dustproof, and has a battery life of up to 60 minutes, meeting the needs of rigorous outdoor missions.
Dual-spectrum fusion imaging:
Integrates 640×512 resolution infrared thermal imaging sensor and 4K visible light camera, supports seamless switching of imaging during day and night, and improves target recognition accuracy by 40%.
AI intelligent tracking:
Based on YOLOv3 enhanced algorithm, it realizes real-time detection and tracking of multiple targets such as human body and vehicle, with a false alarm rate of less than 5%.
Long battery life and anti-interference design:
Equipped with 10000mAh smart battery, the battery life is up to 60 minutes; equipped with a three-band anti-interference communication module to adapt to complex electromagnetic environments.
Multi-scenario expansion interface:
Supports peripheral expansion such as laser rangefinder and gas detection module, and adapts to customized needs such as industrial inspection and search and rescue.
Product Parameters
| Drone Weight | 3.5kg | Target Tracking | Automatic / Manual |
| Transmitter Weight | 4kg | Target Recognition | Automatic (Neural Network Deep Learning) |
| Flight Time | 45min | Find Target Distance | 800m (2.3mx2.3m Target) |
| Voyage | 150km/h | Target Gps Location | Accuracy 30m |
| Flight Radius | 15km | Uav Powered Mode | Electric Propeller (Only One, No Noise) |
| Flight Altitude | 400m | Uav Landing Mode | Parachute |
| Data Link Band | L band (stronger anti-interference ability) | Means Of Transport | Backpack |
| Airplane Mode | Remote control flight/autonomous flight | Size | 792mmx116mmx116mm (Length X Width X Height) |
work principle
Thermal radiation detection
The target's 8-14μm infrared radiation is captured by an uncooled microbolometer (ULIS) and converted into electrical signals to generate thermal images.
01
Dual-spectrum data fusion
Visible light and thermal imaging data are aligned in real time through the FPGA chip to enhance image details and target contour recognition.
02
Dynamic temperature difference compensation
Based on the ambient temperature adaptive algorithm, background thermal noise interference is eliminated to improve the detection sensitivity of low-temperature targets (such as human bodies).
03
Intelligent algorithm processing
Convolutional neural networks (CNNs) are used to segment and classify thermal images to achieve target behavior prediction and alarm.
04
Cloud collaborative analysis
Data is transmitted to the cloud through the 5G module, and thermal distribution modeling and historical data comparison are performed in combination with GIS maps.
05
FAQ
1. What is the maximum detection distance of the device for a standard human body (1.8×0.5m) at 30℃?
When using a 640×512 sensor with a 12μm pixel size, the detection distance can reach 1.2 kilometers (NETD≤50mK).
2. How stable is the drone in rainy and snowy weather?
The fuselage meets the IP67 protection standard and can work stably under conditions of -20℃ to 60℃ and a wind speed of 12m/s.
3. Does it support local data encryption storage?
Supports AES-256 encryption and EU GDPR compliance mode, and optional offline storage module.
4. Can the target recognition model be customized for training?
Provide SDK development kit to support users to import private data sets based on the PyTorch framework for model iteration.
5. Battery fast charging time and cycle life?
Using QC4.0 fast charging technology, it is fully charged in 1.5 hours; the number of battery cycles is ≥500 times (capacity retention rate 80%).
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