One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

Change vector analysis as change detection technique is an effective tool for extracting and identifying land-cover change information from satellite imagery data. Threshold determination is one of most critical task in change vector analysis (CVA) which distinguishes “change” pixels and “no-change” pixels. Many threshold determination techniques for CVA such as empirical strategies, manual trial-and-error procedures or double-window flexible pace search (DFPS) semi-automatic, have been developed since last two decades. But the selection of appropriate threshold determination technique for specific study area is a very important and difficult process because overall accuracy of CVA depends upon threshold value. In this paper, different threshold determination techniques such as empirical strategies, manual trial-and-error procedures and DFPS, have been implemented to evaluate a method for CVA which could more effectively distinguishes the “change” pixels and “no-change” pixels on snow cover area. Experimental results confirm that a semiautomatic DFPS has greater potential than trail-and-error and empirical procedure to determine the specific threshold value for CVA technique that minimizes the overall change detection error probability and maximizes the overall accuracy.