Fusionalt

Fusionalt is a hypothetical framework for real-time fusion of heterogeneous sensor data within distributed edge computing environments. The term combines "fusion" with a suffix implying adaptability, reflecting an aim to unify diverse streams into a coherent situational picture while accommodating varying data quality and latency constraints.

Concept and architecture: In the envisioned model, data from sensors such as cameras, lidar, acoustic, and environmental sensors are abstracted into a common event-based representation. A fusion engine operates in layers: pre-processing and alignment (temporal, spatial, and semantic), core fusion (combining evidence according to probabilistic or consensus-based rules), and post-fusion analytics. The framework emphasizes provenance tracking, fault tolerance, and modular extensibility, enabling plug-in sensors and analytics modules.

Fusion strategies: Fusionalt supports several fusion approaches, including probabilistic fusion using Bayesian inference, conflict-resolving consensus mechanisms, and weighted aggregation that reflects sensor trust and timeliness. It also supports adaptive strategies that adjust fusion parameters in response to observed data quality and latency.

Applications and status: The concept is discussed in theoretical contexts related to smart cities, autonomous systems, robotics, and industrial IoT. In practice, researchers have cited Fusionalt as a design ideal or reference architecture for evaluating data fusion pipelines, rather than a standardized protocol. Implementations remain experimental, with ongoing work on interoperability, security, and resource management.

See also: Data fusion, Sensor fusion, Edge computing, Probabilistic reasoning, Data provenance.