Open AccessMulti‐algorithm Fusion Framework for Energy Prediction of Energy Harvesting IoT Node and Implementation
Author(s) -
Li Xiangyu,
Xie Nijie
Publication year - 2020
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2020.08.011
Subject(s) - computer science , algorithm , internet of things , energy (signal processing) , node (physics) , fusion , sensor fusion , data mining , basis (linear algebra) , real time computing , artificial intelligence , mathematics , embedded system , statistics , engineering , linguistics , philosophy , geometry , structural engineering
Accurate harvested energy prediction of the energy harvesting Internet‐of‐things (IoT) nodes is the basis of the proper power management and should be lowoverhead. A new multi‐algorithm fusion framework, which merges results of multiple prediction algorithms to achieve a higher accuracy, has been proposed. A three‐algorithm fusion solar radiation predictor was implemented. The experiments using the real solar radiation data show that it improves the percentage prediction error by 10%‐26% for different prediction intervals. Its complexity is low enough to run on the embedded systems in real‐time.