This blog is a summary of the discussions from a webinar on “Cloud-Based Analytics Platforms” as part of SSE’s ongoing Decarbonising Buildings series. The cross-industry webinar provided an in-depth discussion on the advantages, concerns, and applications associated with cloud-based analytics platforms, especially in the context of building management, operational efficiency, and sustainability goals.
Services that run computational operations off-premise and deliver actionable insights back to the user. Key benefits include:
Data Storage and Processing Power
The cloud supports large-scale data storage and intensive processing, ideal for analysing vast amounts of building data collected 24/7.
Efficiency
Centralised resources in the cloud deliver cost and operational efficiencies, eliminating the need for on-premise servers and reducing maintenance burdens.
Actionable Insights
Real-time and autonomous data analysis from the cloud can simplify decision-making for customers, especially for benchmarking, reporting, and optimisation.
The discussion highlighted common customer hesitations around security and data privacy when transitioning to the cloud. Key points included:
Addressing Cybersecurity Concerns
Emphasising the importance of selecting providers with strong certifications and explaining what the cloud platforms do and don’t do helps alleviate fears.
Proactive Engagement
IT and cybersecurity teams should be included early in the conversation to align expectations and reduce resistance during the approval process.
Hybrid Solutions
Some customers opt for a mix of on-premise and cloud-based solutions to balance autonomy, resilience, and flexibility.
Cloud-based platforms play a significant role in achieving Scope 1, 2, and 3 emission targets by:
Streamlining Data Access
Automated and live data collection allows for easier tracking of emissions, reducing manual effort and improving transparency.
Energy Efficiency
Cloud solutions consolidate servers, leading to fewer energy-intensive on-premise systems, while centralised data centres can use green energy sources.
Driving Optimisation
Insights from cloud analytics can guide energy-efficient practices, reduce carbon footprints, and promote sustainable operations through benchmarking and forecasting.
Centralised Maintenance and Updates
System updates and firmware patches can be managed centrally by cloud providers, reducing the burden on local teams and minimising the risks of outdated systems.
Scalability
Cloud solutions can handle growing data needs without requiring significant investment in physical infrastructure, which is especially valuable in space-constrained environments like hospitals.
Focus on Core Tasks
By outsourcing data processing to the cloud, on-site teams can concentrate on their primary responsibilities rather than IT maintenance.
- Transitioning from on-premise systems to cloud-based platforms reduces capital expenditure (CapEx) and simplifies operations through subscription-based models.
- Cloud solutions eliminate the need for hardware upgrades and regular maintenance, instead offering continuous updates and security patches.
- Cost savings and operational efficiency make cloud adoption accessible to buildings with legacy systems.
Data as a Currency
As buildings generate increasing amounts of data, cloud-based platforms are expected to play a central role in managing and leveraging this information.
Layered Connectivity
The use of autonomous systems for local management, paired with cloud connectivity for broader data integration, is seen as a resilient and efficient approach.
Machine Learning and AI
Cloud-hosted ML and AI leverage larger datasets, enabling faster, smarter, and deeper insights such as predictive maintenance.
Predictive maintenance benefits include identifying potential failures (e.g., fan vibration anomalies) before they occur by analysing metadata from similar equipment across multiple sites, reducing downtime and repair costs.
Facility managers gain actionable insights, such as identifying top issues by cost impact, optimising resource allocation, and saving energy and carbon.
Energy Optimisation and Carbon Reduction
Larger datasets from multiple buildings enable optimisation across portfolios, identifying anomalies like seasonal or operational differences. Cloud systems support the gamification of data, providing easily understood visuals (e.g., “happy/sad” building statuses) while offering granular engineering details for in-depth analysis. Autonomous systems use data to make real-time adjustments, improving sustainability without human intervention.
Digital Twins
Digital twins offer a virtual representation of real buildings, used in pre-construction for efficiency modelling and post-construction for operational optimisation.
Examples include transforming 2D plans into 3D visuals, enabling engineers to view plant rooms remotely, improving first-fix rates and reducing downtime.
Digital twins foster better energy management, learning, and predictive modelling. For successful implementation, careful design and data integration during construction are critical to maximise comparative analysis and future modelling. Integrating these technologies promotes efficiency, sustainability, and cost-effectiveness across building portfolios while enhancing user and occupant experience.
They also enable simulation and testing in low-cost, low-carbon environments before applying changes to physical buildings.
The industry is moving toward autonomous buildings powered by IoT, AI, and machine learning. These systems will handle real-time adjustments, optimise energy use, and potentially self-heal, though human oversight remains essential.
The focus is shifting away from hardware specifics to interoperability and actionable data insights, regardless of device manufacturer.
- Start by scoping organisational goals, targets, and existing infrastructure.
- Conduct an audit of current systems to identify gaps in data visibility and areas for improvement.
- Benchmark energy consumption and emissions to establish a baseline for tracking progress.
- Use existing hardware and cloud connectivity to begin collecting data, ensuring a low-cost, low-risk entry into the decarbonisation journey.
- Break the journey into manageable steps, prioritising visibility and benchmarking.
- Engage trusted partners and solutions to accelerate progress and navigate complex requirements.
- Collaborate with stakeholders, including technology partners and energy experts
- Maintain flexibility to adjust strategies based on data insights and evolving targets.
The transition to autonomous, decarbonised buildings requires actionable data, cloud-based platforms, and realistic planning. While challenges exist, the industry is poised to achieve significant progress with the right strategies and tools.