This work studies the problem of energy consumption growth in two spheres: Grid-Computing and Smart Environments. These problems are tackled through the establishment of energy-saving policies developed for each environment in order to save the maximum energy as possible. In the Grid-Computing environment, seven energypolicies were designed in an attempt to minimize energy consumption through shutting resources down and booting them. It is proved that approximately 40% of energy can be saved. Efficiency of various grid locations was compared using Data Envelopment Analysis methodology. In Smart Environments where sensors perceive lighting conditions, the energy-saving policy adjusts lighting in order to satisfy user preferences and prevents energy from being wasted. A set of wireless sensors were deployed on two offices at the department of Computer Languages and Systems. The dataset created over several months was employed to extract information about user lighting preferences, from the application of which it is proven that around 70% of energy can be saved in lighting appliances.
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