big data and cognitive computing Article Big Data and Energy Poverty Alleviation Hossein Hassani 1,* , Mohammad Reza Yeganegi 2 , Christina Beneki 3, Stephan Unger 4 and Mohammad Moradghaffari 5 1 Research Institute of Energy Management and Planning, University of Tehran, Tehran 1417466191, Iran 2 Department of Accounting, Islamic Azad University, Central Tehran Branch, Tehran 1955847781, Iran;
[email protected] 3 Department of Tourism, Faculty of Economic Sciences, Ionian University, Galinos Building, 7 Tsirigoti Square, 49100 Corfu, Greece;
[email protected] 4 Department of Economics and Business, Saint Anselm College, 100 Saint Anselm Drive, Manchester, NH 03103, USA;
[email protected] 5 Department of International Relations and Energy Policies, Azad University of Tehran, North Branch, Vafadar Blvd., Shahid Sadoughi St. Hakimieh Exit, Shahid Babaee Highway, Tehran 1651153311, Iran;
[email protected] * Correspondence:
[email protected] Received: 11 June 2019; Accepted: 16 September 2019; Published: 24 September 2019 Abstract: The focus of this paper is to bring to light the vital issue of energy poverty alleviation and how big data could improve the data collection quality and mechanism. It also explains the vicious circle of low productivity, health risk, environmental pollution and energy poverty and presents currently used energy poverty measures and alleviation policies and stresses the associated problems in application due to the underlying dynamics. Keywords: energy poverty alliteration; big data 1. Introduction Energy poverty is a term widely used to define living conditions under unaffordable and inaccessible energy resources. There are a number of factors that cause energy poverty in a broader sense. On the one hand, local factors such as natural resources, geographical location, local policies, household income or education level play an important role in individual energy accessibility and affordability [1,2].