IoT Network Integration

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Summary

IoT network integration is the process of connecting smart devices, sensors, and systems to communicate with each other and with cloud platforms, creating reliable, secure, and scalable networks for data sharing and automation. This integration allows businesses and industries to manage, monitor, and control their operations through seamless connectivity and real-time data exchange.

  • Secure device connections: Always use strong identity verification and encryption to protect IoT devices when connecting them to cloud services and networks.
  • Segment your network: Separate IoT and automation traffic from other business data streams using VLANs or subnets to reduce risks and improve performance.
  • Monitor and automate: Adopt centralized management tools to oversee all devices and automate routine network tasks, making expansion and troubleshooting much smoother.
Summarized by AI based on LinkedIn member posts
  • View profile for Steven Dodd

    Transforming Facilities with Strategic HVAC Optimization and BAS Integration! Kelso Your Building’s Reliability Partner

    31,465 followers

    For a large national corporation with a large number of locations and a third-party hosting location, ensuring the safest, fastest, and easiest network configuration for monitoring and operating various Building Automation Systems (BAS) and IoT systems involves a combination of modern networking technologies and best practices. Network Architecture, Centralized Management with Distributed Control, A robust core network at the third-party hosting location to manage central operations. Deploy edge devices at each location for local control and data aggregation. Use SD-WAN (Software-Defined Wide Area Network) to provide centralized management, policy control, and dynamic routing across all locations. SD-WAN enhances security, optimizes bandwidth, and improves connectivity. Ensure redundant internet connections at each location to avoid downtime. Failover Mechanisms: Implement failover mechanisms to switch to backup systems seamlessly during outages. VLANs and Subnets: Use VLANs and subnets to segregate BAS and IoT traffic from other corporate network traffic. Implement micro-segmentation to provide fine-grained security controls within the network. Next-Generation Firewalls (NGFW): Deploy NGFWs to protect against advanced threats. Intrusion Detection and Prevention Systems (IDPS): Implement IDPS to monitor and prevent malicious activities. Secure Remote Access, Use VPNs for secure remote access to the BAS and IoT systems. Zero Trust Network Access (ZTNA): Adopt ZTNA principles to ensure strict identity verification before granting access. Performance Optimization Traffic Prioritization: Use QoS policies to prioritize BAS and IoT traffic to ensure reliable and timely data transmission. Implement edge computing to process data locally and reduce latency. Aggregate data at the edge before sending it to the central location, reducing bandwidth usage. Ease of Management, Use a unified management platform to monitor and manage all network devices, BAS, and IoT systems from a single interface. Automate routine tasks and use orchestration tools to streamline network management. Design the network with scalability in mind to easily add new locations or devices. Integrate with cloud services for scalable data storage and processing. Recommended Technologies and Tools, Cisco Meraki for SD-WAN, security, and centralized management. Palo Alto Networks for advanced firewall and security solutions. AWS IoT or Azure IoT for cloud-based IoT management and edge computing capabilities. Dell EMC or HP Enterprise for robust server and storage solutions. Implementation Strategy, Conduct a thorough assessment of existing infrastructure and requirements. Develop a detailed network design and implementation plan. Implement a pilot at a few selected locations to test the configuration and performance. Gradually roll out the network configuration to all locations.

  • View profile for Soutrik Maiti

    Embedded Software Developer at Amazon Leo | Former ASML | Former Qualcomm

    7,317 followers

    An IoT device is only as powerful as its connection to the cloud. ☁️ But how do you take an ESP32 project from a local web server to securely communicating with a global service like AWS IoT? I'm excited to share the latest milestone in my ESP32 Captive Portal project: full integration with AWS IoT Core! After a user provisions the device with Wi-Fi credentials through the captive portal, the device now securely connects to the cloud to: ✅ Authenticate using device-specific certificates. ✅ Publish real-time sensor data (temperature & humidity from a DHT22) via MQTT. ✅ Receive commands and updates from the cloud (by subscribing to topics). This turns a standalone device into a manageable, data-producing node in a scalable IoT ecosystem. I've detailed the entire process in the carousel below 👇, from the initial cloud setup to the final line of firmware code. Swipe through to see: ➡️ The high-level system architecture. ➡️ A step-by-step guide to configuring AWS IoT Core (Things, Policies, Certs). ➡️ How to securely manage and embed certificates in your ESP-IDF project. ➡️ Key code snippets for initializing the MQTT client and publishing data. ➡️ The critical role of time synchronization (SNTP) for TLS security. This was a fantastic exercise in building a robust, end-to-end IoT solution. What's your go-to cloud platform for IoT projects, and what's one "gotcha" you've learned along the way? Let's discuss in the comments! Also attaching the link to the repo in the comment section👇 #EmbeddedSystems #IoT #ESP32 #AWSIoT #CloudComputing #MQTT #Firmware #ESPIDF #SecureIoT #Cprogramming #TechProject

  • View profile for Kai Waehner

    Global Field CTO | Author | International Speaker | Follow me with Data in Motion

    38,819 followers

    "Industrial IoT Middleware for Edge and Cloud: The OT/IT Bridge with Apache Kafka and Flink" => Modernization of industrial IoT integration and the shift toward cloud-native architectures. As industries embrace digital transformation, bridging Operational Technology (OT) and Information Technology (IT) has become crucial. The OT/IT Bridge plays a vital role in industrial automation by ensuring seamless data flowbetween real-time operational processes and enterprise IT systems. This integration is fundamental to the Industrial Internet of Things (#IIoT), enabling industries to monitor, control, and optimize their operations through real-time data synchronization while improving Overall Equipment Effectiveness (#OEE). By leveraging Industrial IoT middleware and data streaming technologies like #ApacheKafka and #ApacheFlink, businesses can establish a unified data infrastructure, enabling predictive maintenance, operational efficiency, and smarter decision-making. Explore a real-world implementation showcasing how an edge-to-cloud OT/IT bridge can be successfully deployed: https://lnkd.in/eGKgPrMe

  • View profile for Fahad Shah

    Developer Advocate @ RisingWave | Stream Processing • Iceberg Lakehouses • Real-Time Analytics • Industrial IoT

    5,736 followers

    𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐈𝐨𝐓 𝐰𝐢𝐭𝐡 𝐌𝐐𝐓𝐓 𝐚𝐧𝐝 𝐊𝐚𝐟𝐤𝐚 In the age of Industry 4.0, IoT streaming data pipelines are the backbone of real-time analytics and intelligent decision-making using AI. Integrating MQTT and Kafka bridges the gap between lightweight device communication and robust data streaming, empowering diverse IoT applications. 𝐖𝐡𝐲 𝐌𝐐𝐓𝐓 𝐚𝐧𝐝 𝐊𝐚𝐟𝐤𝐚? ✅ MQTT: A lightweight messaging protocol for communication in constrained networks with limited bandwidth and compute resources using a publish/subscribe model, ideal for IoT applications. Perfect for connected cars, industrial IoT, manufacturing, energy, and logistics. ✅ Kafka: A distributed streaming platform designed for high-throughput, fault-tolerant processing of real-time data streams. It is used to build real-time streaming data pipelines and real-time streaming applications. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 Here’s how you can connect MQTT with Kafka: ➡️EMQX Kafka Bridge: Real-time, bidirectional data bridging. ➡️HiveMQ Enterprise Extension for Kafka: Enables bi-directional data flow. ➡️Confluent MQTT Proxy: Simplifies integration (limited to MQTT 3.1.1). ➡️Kafka Connect: Enables communication with any MQTT-compliant broker. ➡️Custom Development: Flexible but requires significant resources. 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐀𝐜𝐫𝐨𝐬𝐬 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐞𝐬 🏭 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 ✅ Machine connectivity for real-time data collection and monitoring. ✅ Digital twins to simulate and optimize production processes. ✅ Condition-based maintenance to improve operational efficiency. 🔋 𝐄𝐧𝐞𝐫𝐠𝐲 ✅ Optimize electric vehicle charging with dynamic grid systems. ✅ Monitor and control energy usage in smart grids for efficient resource distribution. ✅Enable predictive maintenance of energy infrastructure, reducing downtime. 🚛 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜𝐬 ✅Real-time fleet tracking and route optimization. ✅Predictive maintenance for vehicles and assets. ✅Warehouse automation powered by real-time IoT insights. 🚗 𝐀𝐮𝐭𝐨𝐦𝐨𝐭𝐢𝐯𝐞 𝐈𝐨𝐓 ✅ Real-time telematics for monitoring GPS, fuel usage, and driver behavior. ✅ Predictive maintenance to prevent vehicle failures. ✅ Intelligent traffic systems to reduce congestion and improve efficiency. 𝐓𝐡𝐞 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐟 𝐜𝐨𝐦𝐛𝐢𝐧𝐢𝐧𝐠 𝐌𝐐𝐓𝐓 𝐚𝐧𝐝 𝐊𝐚𝐟𝐤𝐚 By combining MQTT's lightweight efficiency with Kafka's high-performance data processing, businesses can: ➡️ Simplifies real-time IoT data collection, storage, and processing. ➡️ Scale effortlessly to millions of devices ➡️ Build fault-tolerant, future-proof IoT architectures across industries. ✅At RisingWave, both MQTT and Kafka are supported as sources and sinks. Want to Learn More? Follow me (Fahad Shah) and these amazing people: ➡ Andreas VoglerKai WaehnerKudzai ManditerezaSebastián TrolliDylan DuFresne What are your thoughts on integrating MQTT and Kafka in IoT systems? 👇 #IoT #MQTT #Kafka #RealTimeAnalytics #AI #risingwave

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