Cloud-Based Smart Systems

A cloud-hosted Building Automation System (BAS) system-agnostic supervisor offers several benefits for managing a portfolio of buildings: Centralized Management and Monitoring (Single Interface)Provides a unified dashboard to monitor and control multiple buildings, regardless of the underlying BAS systems. This easily scales to include new buildings or systems without significant infrastructure changes. Cost efficiency by reduced IT overhead minimizes the need for on-site servers and IT maintenance. These models often operate on a subscription basis, reducing upfront costs. Enhanced Data Analytics with comprehensive data aggregation that collects and analyzes data from diverse sources to provide insights into energy usage, equipment performance, and occupant comfort. powered by advanced analytics and AI which Utilizes cloud computing power for sophisticated analytics, predictive maintenance, and optimization algorithms. Remote access that allows facility managers to access the system from anywhere with an internet connection. Mobile-Friendly systems support mobile devices, making it easier to manage systems on the go. System Agnostic systems that work with different BAS systems, ensuring compatibility and flexibility in building management and Open Standards should support open protocols like BACnet, Modbus, and others, facilitating integration with various devices and systems. Cloud security benefits from the robust security measures implemented by cloud service providers, including data encryption, regular updates, and security monitoring. leveraging access control by Implementing granular access control policies, ensuring only authorized personnel can access specific parts of the system. Disaster Recovery and Business Continuity, with automatic backups , Regular backups of critical data to ensure minimal data loss in case of a failure. Cloud services offer high availability and redundancy, ensuring continuous operation even during local system failures. Hosted solutions often facilitate sophisticated energy management strategies to reduce consumption and optimize performance. Helping to meet Sustainability goals by providing detailed reports and insights into building performance. The Hosted solution also promotes vendor independence and reduces reliance on a single vendor, allowing for greater flexibility in choosing best-of-breed solutions for specific needs. this Encourages competitive bidding for components and services, potentially reducing costs. Future-Proofing with cloud platforms that are continuously updated with new features and security patches. Hosted supervisors provide access to the latest innovations in BAS technology and smart building solutions. A cloud-hosted, system-agnostic BAS supervisor is not a one size fits all solution but is a compelling choice for organizations managing multiple buildings, enabling them to optimize operations, reduce costs, and improve overall building performance.

If your product just connects devices, you’re building IoT. If it learns, adapts, and acts without you, you’re building AIoT  -  and that’s a different engineering problem. I’ve seen both kinds. The projects that had the biggest gains were the ones that treated intelligence as system design, not an add-on. ➞ IoT Architecture Focuses on sensing, reliable transport, and cloud-based automation. Think sensors -> gateways -> cloud -> dashboards. It’s about connectivity, monitoring, and rule-based workflows using MQTT, HTTP, or CoAP. ➞ Shared Principles Both must deliver secure, scalable, and observable data flows. Minimise latency, enforce consistent schemas, and design for interoperability. But these principles are the baseline, not the differentiator. ➞ AIoT Architecture Adds decision-making inside the stack. Small, quantized models at the edge, local inference, federated training, and feedback loops that turn logs into labels. The outcome: devices that reduce cloud dependency, act in milliseconds, and improve autonomously over time. Practical lessons from the field: ➞ Start with the decision, not the sensor. Define what action you expect the device to take. ➞ Inject structured context. Time, location, device state, and user identity make outputs useful. ➞ Edge-first where it matters. If latency, privacy, or offline capability are required, don’t rely on a cloud round trip. ➞ Build feedback and labeling from day one. Logs are not labels. Capture operator outcomes to close the training loop. ➞ Separate AI suggestions from control actuations. Validate before you execute. ➞ Plan OTA, rollback, and model governance. Updating models in the wild is a release engineering problem. ➞ Design observability for decisions, not just telemetry. If you can’t explain why a device acted, you can’t fix it. ➞ Treat security as foundational. More autonomy increases attack surface. Certificates, encryption, and rotation matter. AIoT isn’t about adding a neural net to your device. It’s about rethinking the entire product lifecycle so systems can think, act, and learn safely and reliably. Where are you pushing intelligence today  -  edge, fog, or cloud? What’s been the hardest part to get right? Repost if you're building for the real world, not just connected demos. ➕ Follow Nick Tudor for more insights on AI + IoT that actually ship.

Cloud AI Architecture This week I’ve been sharing insights on various aspects of AI governance, and today I want to dive deep into one key component - cloud based AI architecture. This example is designed to serve as a guide for any Data/AI leader looking to progress towards responsible AI development and robust governance.   The architecture should be built on layered principles that integrate both global and local regulatory requirements. Here’s a snapshot of what it covers:   Data Ingestion & Quality - Securely collect, cleanse, and store data with built in quality checks and compliance controls to ensure you always have reliable regulated data as the foundation.   Secure API & Service Integration - Expose AI models through secure APIs by leveraging encryption, robust authentication (OAuth, mutual TLS) and proper rate limiting protecting your models against unauthorized access.   Model Training & Deployment - Use containerized environments and automated CI/CD pipelines for scalable and secure model development. Ensure every change is traceable and reversible while continuously monitoring for bias and performance.   Monitoring, Governance & Human Oversight - Implement real time dashboards and detailed audit logs for continuous risk management. Integrate human in the loop controls for critical decision points to ensure that AI augments human intelligence rather than replacing it.   Cloud Security & Compliance - Design your infrastructure with stringent network security, dedicated VPCs, and adherence to data residency regulations. Secure your architecture with encryption, key management, and proactive monitoring.   This layered approach not only mitigates risks like adversarial attacks and data breaches but also supports rapid innovation. It’s a practical scalable blueprint that any organization can adopt to build a secure responsible AI ecosystem.   Want to advance your AI approach? Let's connect and explore possibilities.

Data centers are among the most complex projects in our industry: tight timelines, demanding security standards, and regulatory grey zones. Yet they’ve become essential infrastructure in today’s digital economy. That’s why I love the story below from Drees & Sommer . Their team has reimagined data center planning with a fully cloud-based approach—using @Autodesk Forma as the starting point for integrated, cross-disciplinary collaboration. From site analysis and early layouts to interdisciplinary coordination, Autodesk Forma provides the shared foundation that connects into tools like #Grasshopper, #Revit, and #Veras. The result? Faster feasibility studies, more transparent workflows, and better-informed decisions from day one. This is a powerful example of how cloud-based planning can reduce risk and improve outcomes for some of the most challenging projects in the built environment. 💬 If you could digitize just one part of early-stage planning, what would it be? 🔗 Full story in the comments #AutodeskForma #Cloud #DataCenters #ConnectedConstruction #Sustainability

Stellwerke sind das Nervensystem jeder Bahn. Viele davon sind jedoch reif fürs Technik-Museum. Jetzt kommt frischer Wind in die Branche: Durch digitale Stellwerke aus der souveränen Cloud heben wir gemeinsam mit Hitachi Rail die Infrastruktur auf ein neues Level. Weniger Komplexität, geringere Kosten und deutlich mehr Zukunftssicherheit sind zentrale Vorteile dieser Transformation. Die Digitalisierung bedeutet den Wandel vom mechanischen Schalthebel hin zum intelligenten, cloudbasierten Steuerungssystem. Während klassische Systeme oft noch händisch bedient werden, steuern heute digitale Stellwerke zentrale Prozesse über leistungsfähige Glasfasernetze und vernetzte Datenströme. So könnten im Deutschlandtakt bis zu 30 Prozent mehr Züge auf der bestehenden Infrastruktur fahren – einfach, sicher und effizient. Unsere T Cloud trennt die eigentliche Steuerung von der Technik im Feld und garantiert höchste Sicherheit für Betrieb und Daten. Tests, Updates und Innovationen werden aus der Ferne effizient realisiert, der digitale Zwilling in der Cloud gibt Planungssicherheit und eröffnet neue technologische Möglichkeiten. Insbesondere für kritische Infrastrukturen wie das Schienennetz ist die souveräne, DSGVO-konforme Cloud ein echter Gamechanger. Sie wollen mehr darüber erfahren und die Weichen für die Zukunft stellen? Dann lesen Sie den Experten-Blog von Stephan Kaulbach auf unserem AI & Cloud Web Special: https://lnkd.in/ehUCte4j ***** Signal boxes are the nervous system of every railway. Many of them, however, are ready for the technology museum. Now, fresh momentum is entering the sector: With digital signal boxes in the sovereign cloud, together with Hitachi Rail, we’re taking infrastructure to a new level. Less complexity, lower costs and significantly greater future security are the key advantages of this transformation. Digitalisation means the shift from mechanical levers to intelligent, cloud-based control systems. While classic systems are often still operated manually, digital signal boxes now control central processes via high-performance fiber networks and connected data streams. This approach could enable up to 30 percent more trains to run on the existing infrastructure in the Deutschlandtakt – simply, safely and efficiently. Our T Cloud separates the actual control logic from the technology in the field and guarantees the highest level of security for operations and data. Tests, updates and innovations are efficiently implemented remotely; the digital twin in the cloud offers planning certainty and opens up new technological possibilities. Especially for critical infrastructures like the railway network, the sovereign, GDPR-compliant cloud is a real game changer. Want to learn more and set the course for the future? Then read the expert blog of Stephan Kaulbach on our AI & Cloud Web Special: https://lnkd.in/e59pNqC8 #DeutscheTelekom #TSystems #Digitalisierung #Cloud #AI