Soft Computing, Artificial Intelligence and Applications

Design and Implementation of Smart Cooking Based on Amazon Echo Lin Xiaoguang1,2,3, Yang Yong3 and Zhang Ju1,3 1University of Chinese Academy of Sciences, China 2Chinese Academy of Sciences - Chengdu, China 3Chinese Academy of Sciences - Chongqing, China ABSTRACT Smart cooking based on Amazon Echo uses the internet of things and cloud computing to assist in cooking food. People may speak to Amazon Echo during the cooking in order to get the information and situation of the cooking. Amazon Echo recognizes what people say, then transfers the information to the cloud services, and speaks to people the results that cloud services make by querying the embedded cooking knowledge and achieving the information of intelligent kitchen devices online. An intelligent food thermometer and its mobile application are well-designed and implemented to monitor the temperature of cooking food. KEYWORDS Smart Cooking, Things of Internet, Cloud Services, Smart Home. Original Source URL: ht...

Forecasting Macroeconomical Indices with Machine Learning : Impartial Analysis of the Relation Between Economic Freedom and Quality of Life Jonathan Staufer and Patricia Brockmann Technische Hochschule Nurnberg, Germany ABSTRACT The importance of economic freedom has often been stressed by supporters of liberalism, but can its actu-al effect be observed in a data driven, objective way? To analyze this relation the Economic Freedom of the World (EFW) index and the Human Development Index (HDI) were examined with modern machine learning algorithms and a wide-ranging approach. Considering the EFW index’s preference of a liberal-istic oriented economic policy, an objective recommendation for creating an economic policy that im-proves people’s everyday lives might be derived by the analysis results. It was found that these more ad-vanced algorithms achieve a considerably stronger correlation between both indices than pure statistical means yet leave a small room for interpretati...

Intelligent Electrical Multi Outlets Controlled and Activated by a Data Mining Engine Oriented to Building Electrical Management Alessandro Massaro, Valeria Vitti, Angelo Galiano Dyrecta Lab, Italy ABSTRACT In the proposed paper are discussed results of an industry project concerning energy management in building. Specifically the work analyses the improvement of electrical outlets controlled and activated by a logic unit and a data mining engine. The engine executes a Long Short-Terms Memory (LSTM) neural network algorithm able to control, to activate and to disable electrical loads connected to multiple outlets placed into a building and having defined priorities. The priority rules are grouped into two level: the first level is related to the outlet, the second one concerns the loads connected to a single outlet. This algorithm, together with the prediction processing of the logic unit connected to all the outlets, is suitable for alerting management for cases of thresh...