Military operations depend on intelligence gathering at the edge, where critical decisions have to be made quickly, discreetly, and often without reliable communications. Yet many surveillance systems still rely on an outdated operating model: continuous video transmission from the sensor back to a command center.
That approach made sense when plenty of bandwidth was available and electronic warfare was less sophisticated. But that won’t work in today’s environments. Now, every unnecessary transmission increases the likelihood of detection, while every megabyte of unfiltered video competes for scarce network resources.
Modern missions need to generate intelligence where it is collected rather than after it has been transmitted. At Maris-Tech, we have designed our edge platforms around that philosophy. By combining remote activation software, on-device AI, and metadata-only transmission, our systems allow sensors to remain silent until needed, analyze information locally, and transmit only actionable intelligence.
The Operational Flaw of Always-On Streaming
Continuous streaming creates two major operational problems.
The first is electronic exposure. Every active RF transmission produces a signature that can potentially be detected, analyzed, and geolocated by adversary direction-finding systems. This means that a continuously transmitting sensor can quickly become a target.
The second challenge is bandwidth.
High-definition video generates enormous amounts of data. Tactical radio links, satellite communications, and other constrained wireless networks often cannot handle continuous video feeds from multiple distributed sensors. Valuable bandwidth becomes consumed by raw footage, much of which may never contain actionable intelligence.
For covert missions, such as surveillance, border monitoring, and long-duration reconnaissance, transmitting everything that is captured simply isn’t practical. Instead, intelligence gathering at the edge allows the processing to occur on the sensor itself, so only the information that matters leaves the device.
Maris-Tech’s portfolio of UAV encoder solutions is designed around this operational model, enabling intelligence collection even in highly constrained communications environments.
Intelligence Gathering at the Edge Begins with Silent Deployment
Dormant Deployment — No Emission Until Required
Many tactical sensors spend the majority of their operational life waiting. Traditional systems transmit status information or maintain active communications throughout that waiting period. While convenient, this creates an unnecessary RF footprint.
Maris-Tech approaches deployment differently when it comes to defense and surveillance technologies. Sensors can be positioned well in advance of an operation while remaining electronically silent. They produce no detectable emissions until a validated trigger activates them.
Activation may occur via specific physical conditions (such as motion or vibration detected by the sensor) or an encrypted command sent by operators. Mission-specific rules can also be set up, such as activating only during certain times or when a designated area is entered. Until one of these triggers occurs, the hardware remains dormant and emits no RF signals.
This dramatically reduces electronic exposure while allowing intelligence assets to remain hidden for extended periods before becoming operational.
On-Device AI — Processing at the Source
From Raw Video to Actionable Intelligence
Collecting video is only the first step of an intelligence mission. The system has to then identify relevant objects, classify threats, track movement, and determine which information deserves immediate attention.
Traditional architectures send raw video to a ground station before analysis begins. This creates dependency on stable communications and introduces additional latency.
Maris-Tech eliminates that dependency through on-device AI. Our platforms perform H.265 encoding alongside an integrated AI accelerator directly on the hardware. Object detection, classification, and analysis occur at the point of collection rather than after transmission.
These capabilities are delivered in an ultra-compact platform designed for tactical deployment. With power consumption under 5W and board-level designs weighing approximately 30 grams, Maris-Tech’s edge computing platforms bring powerful AI processing to UAVs, unattended sensors, and other SWaP-constrained applications.
| Operational Layer | Traditional Always-On Approach | Maris-Tech Edge Architecture |
| Transmission Model | Continuous video streaming | Dormant nodes activated only on trigger |
| Processing Location | Ground station dependent | Onboard H.265 encoding with integrated AI accelerator |
| Data Transmitted | Raw full-resolution video | Metadata-only vectors |
| RF Exposure | Continuous broadcast signature | Transmission only when required |
| Power / Size | Larger, higher-power systems | Under 5W, approximately 200g enclosure or 30g board-level |
Metadata-Only Transmission — Cutting Bandwidth Without Losing Intelligence
Transmit Only What Matters
Once onboard AI identifies relevant activity, there is no need to send every video frame across the network. Instead, Maris-Tech converts observations into compact metadata vectors that describe the important intelligence.
These vectors may include object classifications, coordinates, movement patterns, confidence levels, timestamps, or other mission-relevant information. Because metadata is dramatically smaller than full-motion video, it requires only a fraction of the available bandwidth.
Metadata can be transmitted over RF data links, LoRa, Wi-Fi, LTE/5G, or other wireless networks, allowing operators to keep the intelligence flowing even across constrained or intermittent communications. In cases where operators absolutely require video verification, encrypted recordings are securely stored onboard using microSD or eMMC storage.
Intelligence Gathering at the Edge, Anywhere, Anytime
As defense spending reached a record $2.89 trillion globally in 2025, armed forces continue to invest in technologies that provide faster, more secure battlefield intelligence.
By combining remote activation software, on-device AI, tactical edge compute, and metadata-only transmission, Maris-Tech allows defense organizations to deploy sensors that remain covert until required, process intelligence where it is collected, and communicate only what matters.
It’s our motto: Intelligence at the Edge. Anywhere, Anytime, Under Any Conditions.
Learn more about our full portfolio of defense and surveillance technologies to see how Maris-Tech is redefining intelligence gathering at the tactical edge.
FAQ
- What is intelligence gathering at the edge?
Intelligence gathering at the edge refers to the collection, processing, and transmission of tactical intelligence directly at the sensor — without relying on a ground station or central processing hub. Maris-Tech’s edge platforms enable sensors to be remotely activated, analyze video onboard using AI, and transmit only relevant intelligence in real time, even under constrained bandwidth and covert conditions.
- Why is persistent video streaming a liability in electronic warfare environments?
Continuous RF transmission creates a detectable broadcast signature that adversary direction-finding systems can track and locate. In contested or covert environments, persistent streaming is not just inefficient — it actively increases exposure and limits operational flexibility. Maris-Tech’s triggered activation architecture eliminates this risk by keeping systems dormant until operationally required.
- How does remote activation software improve mission security?
Remote sensor activation allows distributed assets to be deployed in advance and remain inactive — generating no RF emissions — until specific physical parameters or command bursts trigger them. Intelligence collection only begins when the mission requires it, eliminating unnecessary exposure during pre-deployment and standby phases. This is the model Maris-Tech’s activation software is built around.
- What are the bandwidth advantages of metadata-only transmission?
Rather than transmitting full HD video streams, Maris-Tech’s systems convert raw sensor data into lightweight metadata vectors containing only the actionable intelligence — object classifications, coordinates, and threat indicators. This dramatically reduces bandwidth consumption and network dependency, maintaining continuous intelligence flow even over narrowband or unstable links.
- How does on-device AI handle automated target recognition?
Onboard H.265 encoding paired with an integrated AI accelerator runs object detection, classification, and tracking directly on the device. Analysis happens at the point of capture — before any data is transmitted — enabling faster target detection and real-time access to actionable intelligence without dependence on a ground processing pipeline. Maris-Tech’s platforms are built around this on-device approach.
- Can edge compute hardware withstand active electronic jamming?
Processing intelligence onboard and transmitting only compact metadata keeps systems operationally effective even when full-bandwidth links are degraded or unavailable. Adaptive streaming technology dynamically adjusts encoding and transmission to maintain communications under constrained or unstable network conditions — this is how Maris-Tech’s hardware is designed for contested environments.
- What is the ideal SWaP profile for an edge intelligence payload?
For covert and tactical deployments, the ideal profile minimizes size, weight, and power without compromising processing capability. Maris-Tech’s Jasper and Coral platforms achieve this with a miniature form factor of approximately 200g within enclosure (30g at board level) and ultra-low power consumption of under 5W — purpose-built for hidden, long-duration deployments.
- How does dedicated hardware accelerate convolutional neural networks?
A dedicated AI accelerator alongside an onboard H.265 encoder enables hardware-level execution of deep learning inference tasks — including convolutional neural networks used for object detection and behavior inference. This hardware-software co-design, which Maris-Tech’s platforms are built on, delivers real-time AI performance at the edge without the power or size demands of a traditional compute system.