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IoT + Edge Computing

Part of our offerings.

Transforming Your Business with IoT + Edge Computing

Unlock real-time insights and enable intelligent actions at the source with Aeologic's IoT & Edge Computing solutions. We design and deploy robust systems that collect data from connected devices, process it locally at the edge for low latency, and transmit essential information to the cloud for further analysis and storage. This approach optimizes bandwidth, enhances security, and enables faster decision-making.

Why Aeologic for IoT + Edge Computing?

Aeologic combines expertise in IoT device management, network protocols, edge computing frameworks, and cloud IoT platforms. We develop end-to-end solutions, from sensor integration to edge analytics and cloud dashboards, ensuring seamless data flow and actionable intelligence for your specific use case.

Key Benefits of Our IoT + Edge Computing

  • Reduced latency for critical decision-making.
  • Lower bandwidth costs by processing data locally.
  • Enhanced data security and privacy by minimizing transmissions.
  • Improved reliability with offline operational capabilities.
  • Scalable solutions from small deployments to large sensor networks.
  • Real-time analytics and alerts from connected devices.
  • Optimized performance for resource-constrained devices.
  • Faster response times for industrial control and automation.

Our IoT + Edge Computing Process

Use Case & Feasibility Analysis

Identifying opportunities for IoT and edge computing, and assessing technical and business viability.

Hardware & Sensor Selection/Design

Choosing appropriate IoT devices and sensors, or designing custom hardware for specific needs.

Edge Computing Architecture Design

Designing the edge processing logic, data filtering, and communication protocols.

IoT Platform & Cloud Integration

Integrating edge devices with IoT cloud platforms (AWS IoT, Azure IoT Hub, etc.) for management and analytics.

Development & Deployment (Edge & Cloud)

Developing software for edge devices and cloud applications, and deploying the solution.

Testing, Monitoring & Optimization

Rigorous testing of the entire system, continuous monitoring, and performance optimization.

Real-World Applications: IoT + Edge Computing Use Cases

Predictive Maintenance for Industrial Machinery (Edge AI)

Predictive Maintenance for Industrial Machinery (Edge AI)

Deployed edge devices with AI models to analyze sensor data locally and predict equipment failures in a factory.

Smart City Traffic Management with Edge Processing

Smart City Traffic Management with Edge Processing

Used edge computing at intersections to analyze video feeds and optimize traffic light timings in real-time.

Remote Asset Monitoring with Offline Capabilities

Remote Asset Monitoring with Offline Capabilities

Developed an IoT solution for monitoring assets in remote locations with intermittent connectivity, using edge storage and processing.

Healthcare Patient Monitoring at the Edge

Healthcare Patient Monitoring at the Edge

Implemented edge devices to process vital signs from wearable sensors locally, providing instant alerts for critical conditions.

Retail In-Store Analytics using Edge Vision

Retail In-Store Analytics using Edge Vision

Deployed edge devices with computer vision to analyze customer foot traffic and behavior within retail stores anonymously.

Agricultural Drone Data Processing at the Edge

Agricultural Drone Data Processing at the Edge

Enabled on-drone processing of imagery for immediate crop health assessment in agricultural applications.

Technologies We Leverage

Latest Insights

Stay updated with our thoughts on technology, industry trends, and innovation.

How to Integrate IOT Devices with Cloud Platforms

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How to Integrate IOT Devices with Cloud Platforms

September 08, 2025

Why IOT Cloud Integration Matters IOT cloud integration is changing how devices, sensors and smart assets interact with...

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The Future of AI in Agriculture: Benefits & Challenges

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The Future of AI in Agriculture: Benefits & Challenges

September 04, 2025

Farming has always evolved—from handtools, to mechanization, to GPS precision farming. However, nowadays it is revolutio...

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Warehouse Automation: How AI Is Driving Efficiency

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Warehouse Automation: How AI Is Driving Efficiency

September 04, 2025

The current environment is tougher than ever before on the warehouses in the modern, hurried around digital economy that...

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AI-Powered Predictive Analytics for Supply Chain

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AI-Powered Predictive Analytics for Supply Chain

September 02, 2025

The global economy is becoming highly competitive and characterized by an increased level of interconnectivity and rapid...

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Frequently Asked Questions (FAQs)

IoT (Internet of Things) connects smart devices, while Edge Computing processes data closer to the source instead of relying on cloud servers. Together, they reduce latency, improve real-time decision-making, and enhance system performance, making applications faster, more secure, and highly efficient.

Edge Computing reduces data transmission to centralized servers by processing information locally. This lowers bandwidth costs, minimizes latency, and ensures real-time responses. For IoT applications like smart cities, autonomous vehicles, and healthcare devices, Edge Computing enables faster insights, stronger security, and more reliable performance.

The integration of IoT and Edge Computing offers benefits like faster data processing, reduced network congestion, improved security, real-time analytics, and cost savings. This combination is essential for mission-critical industries, ensuring devices and applications run smoothly with minimal delays and enhanced scalability.

Industries like manufacturing, healthcare, transportation, agriculture, and retail benefit greatly from IoT and Edge Computing. They enable predictive maintenance, remote monitoring, automation, and smarter decision-making. By processing data at the edge, businesses achieve greater efficiency, lower downtime, and better customer experiences.

Edge Computing improves IoT security by processing sensitive data locally instead of sending everything to the cloud. This reduces the risk of cyberattacks, data breaches, and unauthorized access. Localized processing ensures greater privacy, faster threat detection, and stronger protection for IoT-connected devices.

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