The Future of Spectrum Management
As wireless communications advance, the demand for real-time spectrum management and enhanced RF performance has never been greater. With billions of connected devices, emerging networks and mission-critical operations reliant on uninterrupted, secure signals, traditional spectrum management methods simply cannot keep up.
DeepSig’s OmniSIG® Suite is leading the charge in addressing these challenges via signal classification using AI, and we’re excited to announce the latest advancements: the latest software release of OmniSIG Engine 3.3 and the official launch of OmniSIG Analytics.
Building on the recently released Model Hub, which gives licensed users access to industry-leading AI/ML spectrum sensing models, this update further enhances OmniSIG’s AI-driven signal identification with improvements to Engine 3.3 and Studio 3.3, including:
- Enhanced signal detection and performance
- IQ data handling and output enhancements
- Expanded compatibility and support
- Optimized performance
- New model scoring options
- Improved UI/UX for file handling
Why Analytics Are Essential
The RF spectrum is the foundation of modern wireless communication, supporting everything from smartphones and Wi-Fi to military and satellite communications. However, the increasing complexity of these environments introduces critical challenges:
- Spectrum Congestion: The increase in wireless devices and applications has led to overcrowded spectrum bands, complicating efforts to maintain efficient and reliable communications.
- Security Vulnerabilities: Expanding wireless networks face more significant risks from interference, jamming and malicious attacks, making detecting anomalous behavior critical.
- Operational Efficiency: For organizations with mission-critical operations, like military units or first responders, optimizing spectrum usage is paramount to enhancing performance and minimizing operational costs.
Organizations need tools that don’t just collect data but turn it into actionable insights. That’s where OmniSIG Analytics comes in. DeepSig’s OmniSIG Analytics tackles these challenges head-on by offering an advanced dashboard that delivers deep insights into RF environments, simplifying management, enhancing security and driving operational efficiency. But how does this translate into real-world applications, especially in high-stakes environments like the battlefield?
What is OmniSIG Analytics?
Building on OmniSIG’s AI-driven signal identification capabilities, OmniSIG Analytics introduces big-data analytics and AI to the terabytes of data produced from spectral monitoring.
When a commander asks, “So what? How does this help us make decisions in real-time?” OmniSIG Analytics delivers clear, mission-critical value. The platform’s advanced AI-powered capabilities prioritize threat identification, highlight key anomalies in RF environments, and streamline decision-making by offering immediate, actionable insights. Imagine this scenario: a commander needs to prioritize a list of potential threats in an area with a contested, congested and constrained Electromagnetic Spectrum. OmniSIG Analytics can rapidly classify signals, identify interference or malicious activity, and offer a prioritized list of targets. This process isn’t just about collecting data—it’s about providing targetable, actionable insights that directly influence mission outcomes. Figure 1 below shows the overall health of the analytics platform system and an overview of the information flowing into the system from the sensors.
Figure 1: OmniSIG Analytics Dashboard
The platform delivers tools for constructing a comprehensive spectrum overview, visualizing data, and detecting irregular behavior. It supports seamless integration of multiple OmniSIG sources, from single laptops to enterprise-wide deployments. Key features include:
- 3D Spectral Visualizations
- Trend Analytics
- Rule-Based Anomaly Detection Engine
All of these are available within an intuitive, open-source KIBANA-based dashboard. Designed for flexibility and speed, the AI-powered signal classification is up to 100x faster than traditional methods, continuously improving through machine learning. With support for multi-sensor integration and containerized deployment on any operating system, OmniSIG Analytics enables meaningful, real-time insights from vast RF data.
Key Benefits of OmniSIG Analytics
Abnormal Behavior Detection
The platform continuously monitors RF environments, comparing real-time data with historical patterns to identify deviations that may signal potential threats. Whether detecting unauthorized transmissions or unusual spectrum usage, OmniSIG Analytics provides timely alerts for rapid response.
Figure 2: OmniSIG Analytics – 3D Spectrum
Figure 2 above presents OmniSIG’s 3D Spectrum visualization, illustrating the platform’s output over a specific timeframe. By leveraging rule-based insights, users can identify and highlight anomalies or trends within the spectrum data. The 3D view plots Frequency vs. RSSI vs. Time in a scatter plot where each signal classification type is color-coded; anomalies are separated in their series with diamond-shaped markers, allowing these patterns to stand out visually. This makes it easier to spot unusual behaviors or signals in real time, aiding in more efficient spectrum monitoring and management.
OmniSIG Analytics profiles and establishes baselines for data behavior using statistical models. Integrating these insights into the OmniSIG Suite enhances future threat detection and allows for adaptive, machine learning-driven improvements that ensure ongoing operational security.
Detections and Real-Time Signal Monitoring
In addition to the 3D Spectrum visualizations, OmniSIG Analytics offers a robust detections section, as shown in Figure 3 below, providing users with quick summaries and in-depth insights into signal behavior. As shown in the charts above, the platform tracks various signal types like Bluetooth, LTE, Wi-Fi and more while offering real-time metrics such as RSSI and active signal duration. This lets users observe signal strength trends over time and assess signal activity in congested environments.
More importantly, OmniSIG’s anomaly detection system highlights deviations from normal signal patterns. The Marked Anomalous Annotations Timeline pinpoints when and where abnormal signals occur, giving users a real-time alert system to identify potential threats, interference, or unexpected behavior in the RF environment. This blend of advanced analytics and machine learning helps organizations quickly react to irregularities and make informed decisions on the battlefield or within complex communication networks.
Figure 3: OmniSIG Analytics Detection
Enterprise Scalability
OmniSIG Analytics is designed for scalability, making it suitable for organizations of all sizes, from small businesses to large government and military operations. The platform’s architecture allows easy integration into existing networks, supporting quick and straightforward deployment. Its cloud-native design is ideal for processing large-scale RF data in real-time, whether for local wireless networks or national communication infrastructures.
Fast and Easy Deployment
One significant barrier to adopting new technology is often the complexity of deployment. OmniSIG mitigates this by offering a fast, user-friendly deployment process that doesn’t require specialized hardware or complicated installation.
The OmniSIG Analytics dashboard works seamlessly with OmniSIG, enabling immediate insights into the RF environment. With its intuitive interface and customizable dashboards, teams can quickly get up to speed, minimizing downtime.
A Unified Ecosystem
Together, OmniSIG Analytics, OmniSIG Model Hub and the OmniSIG Engine form a powerful ecosystem for managing RF environments. By combining advanced AI models with state-of-the-art signal processing technology, DeepSig leads the way in next-generation spectrum management solutions.
Discover how OmniSIG Analytics can transform your operations—schedule a demo or learn more on our product page.
