Nowadays, there are many technological-intensive applications that claim to be ¿smart¿. From smartphones to the smart grid, people relate the word smart with technical novelty, automation, enabled communication, and service integration. There is indeed a gap between those smart technologies and their intended ¿intelligence¿; this has arisen an indirect debate between works focusing on automation and mechatronics design and others pursuing a conceptual approach based on fulfilling determinate objectives. One last approach relates the said smartness to deep learning methodologies. In this work, it is attempted to explore both perspectives by providing an overview of recent works around energy usage toward smart cities and the smart grid, pointing out the main conceptual pillars upon which both approaches stand. Certainly, there are enabling technologies supporting the smart concept overall; thus, this work addresses them to characterize ¿smart¿ not from technological or conceptual one-sided viewpoints but from their common backbone. Therefore, the interested reader can find in this work an integrative conceptualization of the smart context, a literature review of recent advances, and a deep discussion of how enabling technologies and current technological trends based on energy consumption are shaping the ongoing efforts toward a sustainable future. More importantly, a new approach to define smart in the said context is elaborated far from the typical misunderstanding of technological nesting or mere usage of ¿advanced¿ digital technologies. Rather, smartness is addressed by the integrative objectives the application pursues, the objectives set by its users¿ intent, and the attained results in terms of public benefit.
