TY - GEN
T1 - An Artificial Intelligence Approach for Time Series Next Generation Applications
AU - Dridi, Aicha
AU - Khedher, Hatem Ibn
AU - Moungla, Hassine
AU - Afifi, Hossam
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - With the emergence of the Internet of Things (IoT) applications, a huge amount of information is generated to help the optimization of operational cellular networks, smart transportation, and energy management systems. Applying Artificial Intelligence approaches to exploit this data seems to be promising. In this paper, we propose a dual deep neural network architecture. It is used to classify time series and to predict future data. It is essentially based on Long Short Term Memory (LSTM) algorithms for accurate time series prediction and on deep neural network, classifiers to classify input streams. It is shown to work on different domains (cellular, energy management, and transportation systems). Cloud architecture is used for IoT data collection and our algorithm is applied on real-time energy data for accurate energy classification and prediction.
AB - With the emergence of the Internet of Things (IoT) applications, a huge amount of information is generated to help the optimization of operational cellular networks, smart transportation, and energy management systems. Applying Artificial Intelligence approaches to exploit this data seems to be promising. In this paper, we propose a dual deep neural network architecture. It is used to classify time series and to predict future data. It is essentially based on Long Short Term Memory (LSTM) algorithms for accurate time series prediction and on deep neural network, classifiers to classify input streams. It is shown to work on different domains (cellular, energy management, and transportation systems). Cloud architecture is used for IoT data collection and our algorithm is applied on real-time energy data for accurate energy classification and prediction.
KW - Artificial Intelligence (AI)
KW - Cloud Applications
KW - Convolutional Neural Network (CNN)
KW - Deep Learning (DL)
KW - Internet of Things (IoT)
KW - Long Short-Term Memory (LSTM)
KW - Time Series Prediction (TSP)
UR - https://www.scopus.com/pages/publications/85089408708
U2 - 10.1109/ICC40277.2020.9148931
DO - 10.1109/ICC40277.2020.9148931
M3 - Conference contribution
AN - SCOPUS:85089408708
T3 - IEEE International Conference on Communications
BT - 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Communications, ICC 2020
Y2 - 7 June 2020 through 11 June 2020
ER -