SAMOS

Research Feature: SAMOS – Smart Antenna Management & Operation Systems

Author: DENOP Research Team
Category: Research
Published by: DENOP (Digital Engineering Technology and Innovation Program), Sekolah Vokasi, Universitas Diponegoro
Tags: #SmartInfrastructure #AIoT #ML #AntennaOptimization #SAMOS #TARA #DENOP

Abstract

SAMOS (Smart Antenna Management & Operation Systems) is the intelligent control and automation layer for next-generation antenna platforms developed by DENOP. Designed as the “brain” of the TARA system, SAMOS leverages Machine Learning (ML) and AI-based models to continuously monitor, analyze, and optimize antenna orientation, signal performance, and network alignment. It interfaces directly with NMS (Network Management Systems) and OSS (Operational Support Systems) to gather telemetry, detect anomalies, and generate adaptive control signals for antenna operations.

Introduction

With the rise of mobile edge computing, 5G, and decentralized digital services, antenna performance and signal integrity have become critical assets in smart infrastructure. Traditional fixed antenna deployments lack adaptability, often leading to signal degradation, interference, or underperformance in dynamic environments.

SAMOS is DENOP’s response to this challenge: an AI-powered, cloud-native autonomous control system that augments signal precision, operational intelligence, and decision-making capabilities in radio access platforms—particularly when paired with TARA (Telecom Anchor Radio Access).

Core Features

1. AI-Powered Optimization Engine
   • Uses Machine Learning models to predict ideal antenna orientation based on real-time telemetry from TARA and connected devices.
   • Integrates with LLM (Large Language Model) engines to interpret complex logs and generate optimization strategies.
2. NMS & OSS Integration
   • Collects signal data, performance metrics, and fault reports from:
     • Network Management Systems (NMS)
     • Operational Support Systems (OSS)
   • Enables end-to-end intelligent decision pipelines.
3. Real-Time Telemetry & Feedback Loop
   • Continuously learns from network environments using self-adaptive algorithms.
   • Supports dynamic antenna steering and auto-tilt for signal optimization.
4. Full Integration with TARA
   • SAMOS acts as the control center for TARA, driving actuator movement based on AI-inferred signal patterns.
   • Provides seamless closed-loop automation in mobile deployments.
5. Cloud & Edge Ready
   • Can be deployed in cloud-native or on-prem environments for both centralized and edge intelligence processing.

Functional Architecture

SAMOS is built on a modular architecture:

• Data Collector Layer: Connects with NMS/OSS to stream network data.
• AI Inference Layer: Utilizes time-series analysis and LLMs for anomaly detection, signal prediction, and performance scoring.
• Control Interface Layer: Sends instructions to TARA’s DC motor systems to adjust azimuth/tilt.
• Dashboard Interface: Provides visualization, manual override, and configuration tools for engineers.

Use Cases

SAMOS is ideal for a wide range of smart infrastructure applications:

• Autonomous Base Stations: Optimizes signal based on AI models, especially in dynamic urban or remote environments.
• Disaster Recovery & Emergency Telecom: Rapid signal alignment in unstable terrain.
• Smart City Edge Networks: Adapts to changing signal loads in real time.
• Telecom Innovation Labs: Supports experimentation with AI-controlled network components.

Strategic Benefits

• Operational Efficiency: Reduces the need for manual antenna alignment and field visits.
• AI-Driven Accuracy: Improves signal coverage and minimizes interference.
• Continuous Learning: Models improve over time with ongoing data ingestion.
• Fault Prediction & Self-Healing: Detects degradations early and recommends/executes adjustments.
• Vendor-Agnostic: Designed to work across various antenna brands and OSS platforms.

Future Development

• Federated learning models for cross-region antenna optimization
• AI-based interference mitigation strategies
• Open API for telecom operator integrations
• Satellite antenna control compatibility

Conclusion

SAMOS brings artificial intelligence directly into the realm of radio infrastructure management. As the cognitive engine of TARA, it is designed to make antenna systems smarter, more adaptive, and increasingly autonomous—forming the foundation for the next generation of intelligent, self-managing network infrastructure.

Contact & More Information

Tito.Bobot@denop.org
sales@denop.co.id
081236087429
www.denop.org