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🌐 𝗜𝗼𝗧 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: 𝗦𝗮𝗳𝗲𝗴𝘂𝗮𝗿𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗪𝗼𝗿𝗹𝗱 𝗼𝗳 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱 𝗗𝗲𝘃𝗶𝗰𝗲𝘀 🔒

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As the number of connected devices grows exponentially, 𝘀𝗲𝗰𝘂𝗿𝗶𝗻𝗴 𝗜𝗼𝗧 𝗲𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺𝘀 has become more critical than ever. This IoT security framework provides a 𝗰𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 to protect devices, data, and users from potential threats. 🔒 𝗞𝗲𝘆 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀 𝗼𝗳 𝘁𝗵𝗲 𝗜𝗼𝗧 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 1️⃣ 𝗔𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗶𝗼𝗻 & 𝗔𝘂𝘁𝗵𝗼𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Secure user access with MFA and SSO, backed by policy engines (PDP & PEP). 2️⃣ 𝗗𝗲𝘃𝗶𝗰𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Secure provisioning, monitoring, and management with actionable Device Analytics. 3️⃣ 𝗗𝗮𝘁𝗮 𝗣𝗿𝗼𝘁𝗲𝗰𝘁𝗶𝗼𝗻: Use PKI for secure communication and SFOTA for safe firmware updates. 4️⃣ 𝗘𝗱𝗴𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Ensure device identity with IDoT and integrate with SIEM/SOC for real-time monitoring. 5️⃣ 𝗟𝗗𝗔𝗣 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Centralized identity and access management for seamless operations. 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗶𝘀...

🏭 𝗙𝗿𝗼𝗺 𝗗𝗲𝘀𝗶𝗴𝗻 𝘁𝗼 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆: 𝗛𝗼𝘄 𝗣𝗟𝗠 𝗗𝗿𝗶𝘃𝗲𝘀 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝗘𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲

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In today's fast-paced manufacturing landscape, 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗟𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 (𝗣𝗟𝗠) serves as the central hub for seamless collaboration and data integration. From design to production and beyond, PLM interconnects with key enterprise systems like 𝗘𝗥𝗣, 𝗠𝗘𝗦, 𝗦𝘂𝗽𝗽𝗹𝗶𝗲𝗿 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀, 𝗮𝗻𝗱 𝗘-𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀, ensuring a unified approach to innovation and execution. 💡 🔗 𝗪𝗵𝘆 𝗶𝘀 𝗣𝗟𝗠 𝗮 𝗚𝗮𝗺𝗲-𝗖𝗵𝗮𝗻𝗴𝗲𝗿? 🌍 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: Bridges the gap between engineering, manufacturing, and procurement teams. 📊 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗗𝗮𝘁𝗮 𝗙𝗹𝗼𝘄: Connects with ERP for accurate cost tracking, inventory updates, and purchase orders. ⚙️ 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝗘𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲: MES integration ensures streamlined workflows and real-time production insights. 🔍 𝗧𝗿𝗮𝗰𝗲𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Tracks compliance and ensures standards with CSM and supplier information. 📈 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻...

🏗️ 𝗘𝗱𝗴𝗲 𝗔𝗜 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱: 𝗛𝗼𝘄 𝗜𝘁’𝘀 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗶𝗻𝗴 𝗦𝗺𝗮𝗿𝘁 𝗙𝗮𝗰𝘁𝗼𝗿𝗶𝗲𝘀 𝗮𝗻𝗱 𝗜𝗼𝗧

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The shift from 𝗟𝗲𝗴𝗮𝗰𝘆 𝗔𝗜 𝘁𝗼 𝗠𝗼𝗱𝗲𝗿𝗻 𝗘𝗱𝗴𝗲 𝗔𝗜 𝗶𝘀 𝗱𝗿𝗶𝘃𝗶𝗻𝗴 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 and efficiency in Industry 4.0. Edge AI processes data locally, enabling faster decisions, dynamic scalability, and optimized costs 🌐. 🌟 𝗠𝗼𝗱𝗲𝗿𝗻 𝗔𝗜 𝘃𝘀. 𝗟𝗲𝗴𝗮𝗰𝘆 𝗔𝗜: ✅ 𝗠𝗼𝗱𝗲𝗿𝗻 𝗘𝗱𝗴𝗲 𝗔𝗜: ⚡ Real-time, on-device processing with minimal latency. ☁️ Scalable model updates with seamless cloud integration. 📉 Reduces bandwidth usage and operational costs. ❌ 𝗟𝗲𝗴𝗮𝗰𝘆 𝗔𝗜: 📡 Cloud-dependent, resulting in higher latency and costs. 🛑 Limited agility for dynamic model retraining. 💡 𝗛𝗼𝘄 𝗘𝗱𝗴𝗲 𝗔𝗜 𝗣𝗼𝘄𝗲𝗿𝘀 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 4.0: 1️⃣ 𝗗𝗮𝘁𝗮 𝗔𝗰𝗾𝘂𝗶𝘀𝗶𝘁𝗶𝗼𝗻: Captures data from sensors and devices (e.g., cameras, GPS, microphones) for local processing. 2️⃣ 𝗢𝗻-𝗗𝗲𝘃𝗶𝗰𝗲 𝗔𝗜 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: Extracts insights and makes decisions directly on edge devices. 3️⃣ 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 & 𝗔𝗰𝘁𝗶𝗼𝗻: Enables real-time re...