title: Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.
abstract: Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.
authors.affiliation: ESAI-Embedded Systems and Artificial Intelligence Group, Escuela Superior de Enseñanzas Técnicas, Universidad CEU Cardenal Herrera, C/San Bartolomé, 46115 Valencia, Spain. juan.pardo@uch.ceu.es.
authors.forename: Juan
authors.initials: J
authors.lastname: Pardo
authors.affiliation: ESAI-Embedded Systems and Artificial Intelligence Group, Escuela Superior de Enseñanzas Técnicas, Universidad CEU Cardenal Herrera, C/San Bartolomé, 46115 Valencia, Spain. francisco.zamora@uch.ceu.es.
authors.forename: Francisco
authors.initials: F
authors.lastname: Zamora-Martínez
authors.affiliation: ESAI-Embedded Systems and Artificial Intelligence Group, Escuela Superior de Enseñanzas Técnicas, Universidad CEU Cardenal Herrera, C/San Bartolomé, 46115 Valencia, Spain. pbotella@uch.ceu.es.
authors.forename: Paloma
authors.initials: P
authors.lastname: Botella-Rocamora