SARAHAI-SERVICE_PROVIDERv6.1
A Telecom AI Agentic Resource for IoT, 5G/SD-WAN, Edge, & Anomaly Detection
1. Introduction & Overview
SARAHAI-SERVICE_PROVIDERv6.1 is an AI-driven platform designed for Telecoms/ISPs to reduce operational costs, proactively detect anomalies, and optimize resources across networks, edge sites, and IoT deployments. It leverages U.S. Patent No. 11,308,384 (Pattern-of-Life + KDE anomaly detection) exclusively licensed to Tensor Networks and includes:
- IoT Device Monitoring & Security (detect compromised devices, unusual traffic/battery usage).
- SD-WAN/5G Slicing Optimization (automatically allocate resources among slices).
- Edge Node Monitoring (Multi-Access Edge Computing, anomalous CPU usage/traffic).
- Fraud Detection (call routing anomalies, billing inconsistencies).
- Capacity Planning (predict throughput usage with ARIMA).
- Pattern-of-Life (PoL) + KDE advanced anomaly detection for user call data and IoT.
- Structured OpenDocument (ODS) Reporting for regulatory or corporate compliance.
2. Key Features & Functions
2.1 IoT Device Monitoring & Security
- IoT Telemetry: Continuously ingests device data (battery levels, firmware, traffic bytes).
- KDE-Based Anomaly Detection: Pattern-of-Life modeling to identify compromised or malfunctioning IoT devices.
- Malfunction Threshold: Set a fraction of anomalies for immediate operator alerts.
2.2 SD-WAN & 5G Network Slicing Optimization
- Slice Data Collection: Gathers usage data (Mbps) for each slice (e.g., LowLatency, HighThroughput).
- Adaptive Allocation: Automatically adjusts resource percentages based on traffic usage and anomalies.
- SLA Assurance: Prioritizes “CriticalServices” or “LowLatency” slices if anomalies or usage surges occur.
2.3 Edge Node Monitoring (MEC)
- Edge Telemetry: Tracks CPU usage, traffic volumes, anomaly scores at distributed sites.
- Federated or Hierarchical: Aggregates local anomaly signals to detect region-wide patterns.
- Proactive Security: Identifies sudden spikes or suspicious usage across multiple edge nodes.
2.4 Fraud Detection
- Single-Metric KDE: Detect suspicious call durations, call routing anomalies.
- Call Data Integration: Ingests call records (caller_id, duration_sec, timestamp, etc.).
- Revenue Protection: Prevents subscription fraud, premium call abuse, out-of-pattern usage.
2.5 Capacity Planning
- ARIMA Forecasting: Predict throughput usage, latency, or general demand across the network.
- Resource Provisioning: Scale up or down virtual network functions or containers based on usage patterns.
- Cost Optimization: Avoid overprovisioning while preventing SLA violations during peak.
2.6 PoL + KDE Anomaly Detection
- Patent 11,308,384: Multi-dimensional Pattern-of-Life plus Kernel Density Estimation.
- Time-of-Day & Usage: Model normal user/device behavior, detect outliers.
- Multi-Modal: Works for call data, IoT data, slice usage, edge metrics, etc.
2.7 OpenDocument (ODS) Reporting
- Data Export: Consolidates call, slice, edge, IoT data into a single ODS file.
- Regulatory Compliance: Compatible with enterprise or government open document standards.
- Customizable: Extend to generate ODT or CSV outputs if needed.
Key Differentiators of SARAHAI-SERVICE_Providerv6.1
- ✅ Pattern-of-Life (PoL) + KDE-Based Anomaly Detection – Exclusive to SARAHAI under U.S. Patent No. 11,308,384, not available in Nokia AVA AI, Google Cloud Telecom AI, or IBM Cloud Pak.
- ✅ IoT Security & Anomaly Detection – Protects telecom-managed IoT devices (smart meters, wearables, cameras, industrial sensors) from botnet hijacking, firmware tampering, or traffic anomalies.
- ✅ 5G & SD-WAN Network Slicing Optimization – Automatically balances resource allocation across slices based on real-time traffic demand and behavioral analysis.
- ✅ Multi-Access Edge Computing (MEC) Node Security – Identifies regional-wide edge threats by aggregating MEC anomaly scores, ensuring distributed AI threat monitoring.
- ✅ Autonomous Fraud Detection for Telecom Operators – Detects call routing anomalies, subscription fraud, and predictive billing inconsistencies.
- ✅ Hybrid AI Execution (CPU+GPU Processing) – Runs AI-powered anomaly detection at both cloud-scale and edge scale for real-time event processing.
- ✅ Structured OpenDocument (ODT/ODS) Telecom Reporting – First telecom AI system to support OpenDocument formats, ensuring compatibility with government, enterprise, and compliance-driven reporting requirements.
- ✅ Privacy-Preserving AI for Telecoms – Unlike cloud-based alternatives, SARAHAI enables fully local processing of AI models, ensuring compliance with GDPR, CCPA, and Zero Trust frameworks.
Why Choose SARAHAI-SERVICE_Providerv6.1?
- Designed for Modern Telecoms & ISPs – Handles IoT, Edge, 5G Slicing, SD-WAN, and MEC Security in a unified AI-driven framework.
- Autonomous, AI-Optimized Network Operations – Enables real-time AI automation, reducing OPEX and improving SLA compliance.
- AI for IoT, SD-WAN, & 5G Security – Monitors 50K+ IoT devices, MEC nodes, and network slices per instance, with seamless scaling.
- Industry-Exclusive AI Features (Patent 11,308,384) – Uses PoL-based anomaly detection with KDE for behavioral modeling unmatched by competitors.
SARAHAI-SERVICE_Providerv6.1 is the most advanced AI-driven operational intelligence solution for telecoms, outperforming Google Cloud Telecom AI, IBM Cloud Pak, and Microsoft Azure AI in real-time network slicing, MEC security, IoT monitoring, and fraud detection.