The prodigious rise in consumer electronics and advanced low-cost manufacturing techniques have increased the human-device interaction in daily life. This interaction has led researches on the concept of Internet of Things (IoT) to raise the quality of life in all manner. However, communication between these "things" reduces their lifetimes because of the battery limitation. Due to this reason, energy efficiency has became one of the most important challenge in IoT. In many recent studies, even though this main challenge has been addressed with different aspects, most of all these solutions have compromised the coverage area for energy efficiency. Beside coverage losses, most of the proposed frameworks demand human control and interaction during fail recovery. The energy efficiency and minimization of human interactions should be handled simultaneously in IoT frameworks for more effective deployments. Additionally, the total covered area, distribution of devices and the distribution of events have to be taken into account to successfully manage the network. Having this motivation, we propose an energy efficient Self Organized Things framework, SoT. The proposed SoT uses an optimization procedure in order to minimize the overall energy consumption of the things, while stabilizing the total coverage area. Moreover, the human dependency is overcomed in SoT by re-defining the next generation self-configuration, self optimization and self-healing procedures of self-organizing network structure of Long-Term Evaluation (LTE) systems. In this self-management process of the SoT, specific spatial distributions of devices and intersections of their coverage areas are also analytically derived. Here the spatial distribution is used to determine the distribution of the active things in 2D space. To increase the efficiency, the remote devices are activated and the event observation rate is maximized. By definition the "event" is a special attribute that the things are observing. In addition to spatial distribution in SoT, a conflict parameter, that calculates the intersection of devices' coverage areas, is also proposed to enlarge the coverage area. Using this conflict parameter, the selection of overlapping things is prevented and the actual covered area is maximized. By increasing the actual covered area, the probability of observing an event is increased. Consequently, the performance of the proposed SoT framework is measured in terms of the total covered area per energy and network's lifetime. The through evaluation results verify that proposed framework increases the lifetime of network 150%. (C) 2014 Elsevier B.V. All rights reserved.