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Background subtraction, being the most cited algorithm for foreground detection, encounters the major problem of proper threshold value at run time. For effective value of the threshold at run time in background subtraction algorithm, the primary component of the foreground detection process, motion is used, in the proposed algorithm. For the said purpose, the smooth histogram peaks and valley of the motion were analyzed, which reflects the high and slow motion areas of the moving object(s) in the given frame and generates the threshold value at run time by exploiting the values of peaks and valley. This proposed algorithm was tested using four recommended video sequences, including indoor and outdoor shoots, and were compared with five high ranked algorithms. Based on the values of standard performance measures, the proposed algorithm achieved an average of more than 12.30% higher accuracy results. [ABSTRACT FROM AUTHOR]

The existing research is about location tracking either completely indoor or altogether on open air by utilizing various sensors and procedures based on inter-networking or internet of things. A limited arrangement has been proposed to embrace a single location area detecting innovation that based on both environments using physical devices. This paper intends to track a client position in both indoor and open-air situations by utilizing a single remote sensor with negligible subsequent bumble. The huge majority of the existing localization arrangements use additional equipment supplies to accomplish higher limitation precision. Received signal strength indicator (RSSI) was the standard element of remote sensors; the localization methods won't have any extra equipment. To overcome the problems, we need to study how to grow more precision distance for the strength of the signal model and 3dimensional measurement techniques. The Path Loss Exponent (PLE) determines the separation of RSS. In this event that RSS diminish at the separation, PLE will measure the rate; its esteem depends on the extraordinary proliferation environment. For positioning, the system requires location data. Most part use two-dimensional positioning as a part of the system with moving toward localization with three-dimensional positioning with weighted centroid restriction calculation as a proposed work. Here considers the triangular pyramid to perform three-dimensional positioning instead of three circle intersection method, in which the pyramid is divided into four two-dimensional surfaces. It consists of different parts of the environment where transmitter and receiver’s parts have the different PLE when compared to others existing research. Many researchers used two-dimensional positioning system, however, some circumstances we have to go through in three-dimensional position system. So, the proposed idea is basically based on the three-dimensional centroid limitation of systems. [ABSTRACT FROM AUTHOR]

Cloud computing is a recent tendency in IT that moves computing and data away from desktop and hand-held devices into large scale processing hubs and data centers respectively. It has been proposed as an effective solution for data outsourcing and on demand computing to control the rising cost of IT setups and management in enterprises. However, with Cloud platforms user’s data is moved into remotely located storages such that users lose control over their data. This unique feature of the Cloud is facing many security and privacy challenges which need to be clearly understood and resolved. One of the important concerns that needs to be addressed is to provide the proof of data integrity, i.e., correctness of the user’s data stored in the Cloud storage. The data in Clouds is physically not accessible to the users. Therefore, a mechanism is required where users can check if the integrity of their valuable data is maintained or compromised. For this purpose some methods are proposed like mirroring, checksumming and using third party auditors amongst others. However, these methods use extra storage space by maintaining multiple copies of data or the presence of a third party verifier is required. In this paper, we address the problem of proving data integrity in Cloud computing by proposing a scheme through which users are able to check the integrity of their data stored in Clouds. In addition, users can track the violation of data integrity if occurred. For this purpose, we utilize a relatively new concept in the Cloud computing called “Data Provenance”. Our scheme is capable to reduce the need of any third party services, additional hardware support and the replication of data items on client side for integrity checking. [ABSTRACT FROM AUTHOR]