PowerMa

PowerMa is a power management framework designed for embedded and mobile computing platforms. Developed by the Institute for Energy Efficient Systems, the framework provides a unified set of algorithms that enable real‑time optimization of device power consumption without sacrificing performance. PowerMa operates through a layered architecture: a hardware abstraction layer exposes device sensor data, a decision engine processes usage patterns using machine‑learning models, and a policy interface applies power‑saving states such as dynamic voltage and frequency scaling, sleep modes, and peripheral shutdown.

The framework was first released in 2015 as an open‑source project under the Apache 2.0 license. It has since been adopted by major smartphone manufacturers and IoT vendor companies to extend battery life and reduce thermal output. One of PowerMa’s distinguishing features is its predictive scheduling algorithm, which learns daily user activity and pre‑emptively adjusts workloads for peak battery efficiency. The system also supports fine‑grained control of individual components, allowing developers to specify trade‑offs between speed, accuracy, and power consumption.

PowerMa’s API is platform‑agnostic, with bindings for C, C++, and Python. Comprehensive documentation and example projects are maintained on the project's GitHub repository. The framework has been cited in academic conferences such as IEEE Micro and ACM MobileHCI for its contributions to sustainable mobile computing.