232 Sustainable IT tools indexed in the toolbox
Welcome to the INR tool box that presents a list of Sustainable IT tools. Our goal for 2022 is to optimize this list: to improve the methodology for selecting tools and to cover all Sustainable IT themes.
If you have any suggestions for Sustainable IT tools or would like to get involved with us to help us optimize the toolbox, please write to us: outils-nr [@] institutnr.org
Explore a quickview of indexed tools in the Sustainable IT toolbox
Powerapi
PowerAPI is a middleware toolkit for creating software-defined power meters. Software-defined power meters are configurable software libraries that can estimate software power consumption in real time. PowerAPI supports the acquisition of raw metrics from a wide variety of sensors (e.g. physical meters, processor interfaces, hardware counters, OS counters) and the provision of power consumption through different channels (including file system, network, web, graphics). As a middleware toolkit, PowerAPI offers the ability to assemble “à la carte” power meters to meet user needs.
Toovalu
Toovalu is a simple tool allowing you to manage and communicate your performance in terms of GHG Balance (Greenhouse Gas) and, more broadly, social responsibility. Toovalu allows you to: simplify and systematize the production of your Bilan Carbone ®, facilitate the management and communication of your CSR performance ...
The sdgs are not complicated
Reconciling commitments and economic performance is possible, it is even a source of opportunities and it is necessary for your performance to be sustainable. Discover in a simple and fun way through 7 short video sketches the strong links existing between your business challenges and the SDGs (Sustainable Development Goals).
Https everywhere
HTTPS Everywhere is a Firefox, Chrome and Opera extension that encrypts communications with many websites making browsing more secure.
Adversarial robustness toolbox
Python library for machine learning security. ART provides tools that enable developers and researchers to defend and evaluate learning (ML) models and applications against adverse threats. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video , etc.) and machine learning of tasks (classification, object detection, voice recognition, generation, certification, etc.).