Low-Altitude Economy | JHCTECH Edge Computing Empowers Drone Detection and Identification
The market prospects for drones are extensive. Small drones can be widely utilized in fields such as aerial photography, agricultural crop protection, disaster prevention and mitigation, search and rescue, traffic monitoring, resource exploration, remote sensing and mapping, border patrol, meteorological observation, and more. However, the lag in drone management and control measures has led to numerous “unauthorized flights” that are difficult to regulate and hold accountable, creating an urgent need for drone detection and countermeasure solutions.
The development and illegal misuse of drone technology have brought significant security risks and threats to critical defense areas, including border security, battlefields, coastal defense, airports, nuclear power plants, public safety, prisons, energy infrastructure, and key tourist attractions. These issues have resulted in substantial economic losses and seriously undermined low-altitude airspace safety. Drone detection and countermeasures play a vital role in safeguarding low-altitude airspace security.
Drone Detection and Identification
Drones are classified as “low, slow, and small” targets. They typically operate at low and ultra-low altitudes, have slow flight speeds, and are challenging to detect. This presents significant challenges for target detection. Drone detection and identification is a multidisciplinary application technology that leverages one or more technologies such as radar detection, radio signal monitoring, optoelectronic identification and tracking, and sound monitoring to achieve effective detection, tracking, and identification of drones.
From a technical perspective, traditional single detection methods are insufficient to handle all scenarios effectively and accurately. A multi-dimensional collaborative detection approach is typically employed, combining “radar + wireless + optoelectronics” to achieve precise detection and tracking of targets in low-altitude airspace. Radar systems can scan wide airspace areas and capture information such as the drone’s flight trajectory, speed, and altitude. Wireless detection monitors communication signals between the drone and its remote controller or ground station to obtain control commands and flight status. Optoelectronic identification and tracking systems use optical and infrared sensors to achieve high-precision and high-sensitivity tracking and positioning of drones.
User Application Requirements
A Chinese expert specializing in precision anti-control of drones provides users with an integrated drone detection and countermeasure solution. They approached JHCTECH to find a high-performance edge computing box for their optoelectronic identification and tracking system to enable high-precision, high-sensitivity tracking and positioning of targets in low-altitude airspace. The following capabilities are required:
⭐ High-efficiency CPU performance to support the operation of customer-developed software models;
⭐ Rich IO interfaces for connecting to optoelectronic identification equipment;
⭐ Powerful expansion capabilities, including support for GPU card integration, enabling in-depth image data analysis and precise inference
⭐ Wired and wireless communication capabilities to ensure real-time data transmission.
JHCTECH Solutions
Finally, two JHC edge computing products were selected: KMDA-5920 and BRAV-7720. These products support the customer’s self-developed optoelectronic identification and tracking system model, enabling high-precision and high-sensitivity tracking and positioning of drones. JHCTECH edge computing solutions are primarily used to receive data captured by optoelectronic cameras, achieving precise drone positioning.
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The following is a sharing of the BRAV-7720 solution.
The BRAV-7720 is equipped with Intel® Alder Lake-S/Raptor Lake-S series. For this project, the I7-12700 CPU was selected, providing the high performance necessary to support the efficient operation of the customer’s self-developed optoelectronic identification and tracking system model. With dual-channel DDR5 memory slots, it supports up to 64GB, meeting the user’s operational requirements. Its comprehensive I/O functionality includes 3*LAN, 6*USB3.2, and 2*COM ports, ensuring seamless connections with optoelectronic identification equipment. Additionally, its 8K DP and 4K HDMI dual independent display outputs enable efficient real-time visualization of drone positions.
The system features dual PCIe expansion slots: one PCIe X16 (X16 signal) supporting up to a 450W GPU card or a 75W AI accelerator card, and another PCIe X16 (X4 signal) supporting a 75W AI accelerator card. For this project, an RTX 3070 Ti GPU card was selected. The GPU processes drone images using deep learning algorithms such as convolutional neural networks, automatically identifying key features such as drone models, manufacturer information, and flight intentions. It also analyzes and predicts drone flight trajectories and behavioral patterns. When the system identifies a potentially threatening drone, it automatically activates defense and countermeasure mechanisms. These include electronic interference, electromagnetic suppression, and directional RF attacks to precisely control the drone. The countermeasures dynamically adjust strategies based on the drone’s type, flight altitude, speed, and other factors. For instance, specific frequency electromagnetic interference signals can disrupt the drone’s control system or communication link, forcing it to lose control or land.
Additionally, the BRAV-7720 has high PFC power efficiency, a high-efficiency cooling solution, and an industrial-grade reliability design, ensuring the system operates continuously and stably 24/7.
BRAV-7720
▪ Intel® 12th/13th generation Alder lake-S/Raptor lake-S LGA1700 series CPU
▪ Intel® Q670 chipset
▪ 2*DDR5 4800MHz SODIMM, up to 64GB
▪ 1*DP+1*HDMI and 1*VGA, ultra-high-definition 8K+4K triple independent display
▪ 2*Intel® I226V Gigabit network, 1*Intel® I219LM Gigabit network, support iAMT12.0
▪ 1*PCIe X16 (X16 signal)+1*PCIe X16 (X4 signal)
▪ 2*2.5”SATA3.0 Bay, 1*M.2 2280 PCIeX4 NVMe
▪ Support TPM2.0 security encryption and iVpro technology
▪ CPU fanless cooling, AI/GPU card efficient air cooling design
▪ Support 450W GPU or dual 75W/150W AI accelerator card power supply
▪ 1000W PSU DC 12V power supply, standard high PFC wide temperature fanless, AC-DC power adapter
KMDA-5920
▪ Intel® 8th/9th generation Coffee lake LGA1151 series CPU
▪ Intel® H310 chipset
▪ 2*DDR4 2400/2666MHz SODIMM, up to 64GB
▪ Support 1*DP, 1*HDMI and 1*VGA triple display
▪ 2*LAN, 4*USB3.1, 2*USB2.0, 16bit Iso. DIO
▪ 2*RS232/422/485 and 2*RS232 quad serial ports
▪ 1*PCIeX16 and 1*PCIeX16 (X4 signal) dual expansion
▪ 1*M.2 E-key 2230, Supports Gigabit WIFI module
▪ 2*2.5-inch SATA3.0 easy-swap hard disk slots and 1*mSATA
▪ Wide voltage DC 9-36V power supply, with short circuit, overvoltage and overcurrent protection
Learn more about BRAV-7720 series
Learn more about KMDA-5920 series