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Overview

This Guidance demonstrates how to integrate building systems, assets, and sensors to enable real-time and historical insights for sustainable building management.  Operations data from sources such as HVAC, water, electricity, and solar power are consolidated and processed with artificial intelligence and machine learning (AI/ML) capabilities. The data is stored, analyzed, and visualized to reveal where and how buildings are generating emissions across their infrastructure and operations. Customers can also deploy their own sensors, on their own networks, and quickly show which buildings are driving the greatest emissions across their global environment.

How it works

Integrate building systems, assets, and sensors to enable real-time insights for sustainable management across your infrastructure and operations.

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Sample code

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Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

CloudWatch provides centralized logging with metrics and alarms across all deployed services to raise alerts for operational anomalies. For example, you can create an alert to prompt for a service limit increase if you surpass a threshold of concurrent Lambda executions or active Kinesis Data Firehose partitions.

Read the Operational Excellence whitepaper 

Resources are protected using AWS Identity and Access Management (IAM) policies and principles. Use least-privilege access and role-based access to grant operators permissions to modify resources, such as deploying an updated stack through AWS CloudFormation.

AWS Key Management Service (AWS KMS) encrypts your data at-rest in Amazon S3 and AWS IoT SiteWise. AWS KMS encrypts your data in-transit with Lambda and Kinesis Data Firehose. The keys should be rotated on a regular schedule.

Read the Security whitepaper 

This Guidance uses AWS services that are serverless, enabling auto-scaling to respond to fluctuating demands. For example, AWS IoT Core, AWS IoT SiteWise, and Kinesis Data Firehose scale to match the throughput of your data with no management required. For in-flight processing, Lambda will automatically scale the number of execution environments required to handle demand. 

AWS services are used to provide various options for data backup and recovery. For example, Amazon S3 has object versioning, replication, and backup features to ensure Recovery Point Objectives (RPOs) can be met. If needed, AWS IoT SiteWise APIs can provide definitions of assets and models for easy backup and restoration. 

Read the Reliability whitepaper 

Services in this Guidance were purposefully selected to handle the needs of a modernized building management system. Amazon S3 was selected for its reliable long-term storage and flexibility of consuming tools and services. AWS IoT SiteWise provides managed, scalable ingestion, and real-time calculation of streaming asset data, minimizing the need to build custom components. It integrates seamlessly with AWS IoT TwinMaker, which was chosen for digital twin creation.

Read the Performance Efficiency whitepaper 

This Guidance relies on serverless AWS services such as AWS IoT TwinMaker, AWS Glue, Lambda, Athena, and Kinesis Data Firehose. These services are fully managed and autoscale according to workload demand. As a result, you only pay for what you use.

Read the Cost Optimization whitepaper 

Data in Amazon S3 can be stored in more efficient file formats (such as Parquet) to prevent unnecessary processing and reduce the overall storage required.

Amazon S3 lifecycle policies can automatically move data to more energy-efficient storage classes, enforce deletion timelines, and minimize overall storage requirements. 

This Guidance uses managed, serverless technologies such as AWS Glue, Lambda, Athena, and Step Functions to ensure hardware is minimally provisioned to meet demand.

Read the Sustainability whitepaper 

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

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