Case Study Submissions
CAST Use Case
Overview CAST used a combination of the SCI formula and its own automated software intelligence technology (CAST Highlight) to measure the estimated reduction in carbon emissions after decarbonizing a software application.
The results show that decarbonizing a single application could potentially reduce annual CO2 emissions by an estimated 400 kg.
These results are being used to develop a model within CAST Highlight that can be used to automatically estimate the potential CO2 emissions savings for any application.
A summary of the story is also attached as a PDF for reference in addition to the the details provided as part of this template.
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DOW / Microsoft submission - Graph DB Use Case
Over view
Collaborative use case with Dow and Microsoft performed by Tammy McClellan and Srinivasan Rakhunathan from Microsoft. Eric Friedeberg, Brandon Smith, and Samantha Beauchamp from Dow.
Solution chosen is a current solution in development and is the measurement of carbon in both Neo4J and TigerGraph graph databases. Information was collected via load tests by calling an API deployed in an app service.
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NTT DATA - On-Premise Web system
Overview
We calculated SCI value for a web system following 3-tier architecture. Calculating SCI value through this case study involves measuring the behavior of components and their results based on scenarios. We deployed TPC-W implementation proposed by Transaction Processing Performance Council as a workload. TPC-W is designed for measuring performance and cost for performance in an environment where online transaction processing (OLTP) is set up for e-commerce. In areas where it is difficult to measure, it is estimated by publication from trusted institutions. We assume life span of this system is 4 years, then M is divided by 35040 [hours] (4 [years] 365 [days] 24 [hours])
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Microsoft - Ecommerce web application using eShoponWe
Overview
The application is a web application that is used in an ecommerce scenario by customers. It is a sample ASP.NET Core reference application, powered by Microsoft, demonstrating a single-process (monolithic) application architecture and deployment model.
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Microsoft - GreenAI
Overview
Machine Learning training consumes vast amounts of energy. In this test case, we will calculate the SCI delta between two convolutional neural networks (InceptionV3 and DenseNet) for an image classification scenario.
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Farm-insights-Raspberry-Pi
Overview
.NET Core application running with temperature, humidity, sunlight, and soil moisture sensors. Running headless on a raspberry pi. I purchased a power meter and had the pi plugged into it. Ontology is device only.
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Aveva Case Study
Overview
This document describes a system that can accurately measure the energy consumption of application software. Instead of relying on energy measurement circuits that are integrated into the computer’s motherboard the whole computer is treated as a black-box and the electrical energy provided to the device is accurately measured using a high-precision benchtop power supply. The precision of the energy measurements is 0.01 Watts. The first part of the document describes the hardware and software architecture of the system. It provides all the necessary details to build a complete system. Part 2 covers a typical use case and workflow for measuring the energy consumption of a software product.
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Endava-Fraud Detection API case study
Overview
We analyzed a fraud detection tool, deployed and maintained by our organization, which scans online transactions and gives it a risk score.
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UBS SCI case study
Overview
This document describes the testing the SCI of two software applications. The first software application is for an Investment Bank and the other in Asset Management. We wanted to baseline the carbon emissions for these two software applications, to determine the data that is currently available in the organisation for the calculations.
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Automated SCI Measurements with Green Metrics Tool
Overview
The Green Metrics Tool (GMT) is an open-source software solution that provides the capabilities of automating the process of generating an SCI metric for a given piece of software.
The GMT is essentially a container native benchmarking tool that instruments a software according to a so called usage scenario. Which describes the usual interaction with the software in an computer executable fashion. While executing this scenario different measurement sources are polled like machine energy, cpu energy, network traffic etc. and then put into context with a unit of work.
When supplying the basic input variables to the SCI like (I, EL, RS, TE) and instrumenting the software so that it outputs the unit of work variable (R) to a standard output stream the tool automatically generates the SCI metric.
All of this instrumentation is fixated in a typical DevOps like standard infrastructure as code (for instance Docker compose files) and can be part of the git repository. Thus, businesses can seamlessly integrate carbon footprint assessments into their software development pipelines, fostering a culture of sustainability.
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Trustwise-case-study
Overview
In the insurance industry's dynamic landscape, companies are increasingly leveraging generative AI to enhance customer service, streamline claims processing, and develop predictive models for risk assessment. However, the deployment of these AI models comes with significant energy and carbon costs, raising concerns about their environmental impact and operational efficiency.
The ISO SCI 1.0 standard offers a framework to address these challenges by providing guidelines for sustainable computing. This use case aims to demonstrate the practical implementation of the ISO SCI 1.0 standard in a high-stakes, real-world scenario within the insurance sector.