Search Results for "framework for sensor data aggregation" - Page 2

xAffect is a software framework for online recording, processing and storage of multi sensor data. It was developed at FZI Research Center for Information Technology, Karlsruhe, Germany. xAffect can be used as a flexible, customizable middleware between physiological sensors and applications which require online feature computation (e.g. biofeedback or affective computing).

Sensor Framework provides applications with of multi-access sensor hardware (eg. accelerometer, compass, ambient light sensor). With Sensor Framework, applications don’t to know the device’s specific information or talk directly to the driver. Its ho

Heimdall is a sensor fusion framework. It uses a component-based approach to create a sensor fusion middleware. This is the core component, which controls the interaction between the components used to do the sensing and the processing of data.

MutanT is an cross platform framework for performing multi-sensor data processing. It is not limited to any specific task but can be extended arbitrarily by users and developers. Data processing is performed by a chain of filters, a use can combine.

SpyGlass is a modular and extensible visualization framework for wireless sensor networks.

motes-app is a web based data aggregation and monitoring tool for MDA320 and MDA300 sensor boards motes and base station.

SIRS stands for "Smart Indicators for Reflection Support". SIRS is a framework for developing Indicators on top of sensor networks in web-based and ambient environments for data aggregation, information visualization and context adapation.

SALi is a framework for computation that decouples applications that use sensor data from actual sensors, and provides additional functionality such as attribute based sensing and sensor simulation.

MobHealth is an extensible mobile health framework/API written in JavaME. The current version supports two sensor-data formats (e.g. used by AliveTec). It already provides higher-level classes for data recognition like body position or hypoxia-detection.

A feedback-enhanced framework for routing in wireless sensor networks. Speeds up the process of implementing routing techniques. Enables piggybacking of routing information on data packets. Written for the Omnet++ simulator and the Mobility Framework.

Java framework for real time data collection, aggregation and manipulation. This top level project is composed of different sub-projects.

CortexBrain is a cutting-edge data simulation and big data analysis framework developed by CortexFlow, designed to simplify the simulation and analysis of IoT (Internet of Things) devices. CortexBrain enables you to model and train various IoT sensor properties, including smart lights, accelerometers, gyroscopes, and temperature sensors. With CortexBrain, you can simulate IoT sensors, position them on a geolocalized map, monitor key metrics, and simulate specific scenarios.

Framework to simplify developing applications that use wireless body sensor networks (bodynets). Manages sensor sampling, data buffering, local processing and communication. Supports embedded devices running TinyOS and any Java-capable gateway.