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Localization services within Ambient Assisted Living systems often require expensive phases of environment setup and devices calibration/configuration. This research aims to propose innovative methodologies and tools able to keep such phases as simple as possible, looking for low complexity as well as low cost approaches. Localization and tracking techniques that exploit Wireless Sensor Network (WSN)...
This paper presents the porting activities related to a famous agent-based middleware (MW) for Wireless Sensor Networks (WSN), i.e. Agilla. After discussing main WSN-MW features, the paper describes in detail the procedure used to port such a MW from TinyOS 1.x to TinyOS 2.x. The porting has been successfully completed and then validated by means of several Agilla applications. The new code, called...
Crazy Square is an interactive environment for music learning that is specifically developed for children approaching music and a musical instrument for the first time. Audio signal processing algorithms are required for the game to work properly such as pitch detection and beat detection. In this paper an analysis of Pitch Detection Algorithms (PDAs) responding to Crazy Square requirements is presented...
Indoor range-based localization algorithms often require a noticeable computational effort and, even providing a good precision, cannot always fit on a limited-resource device of a Wireless Sensor Network (WSN). This paper proceeds a previous work that has investigated the reachable precision of a lightweight localization based on Received Signal Strength (RSS). This time the focus is put on a real...
Localization systems based on Wireless Sensor Networks (WSNs) have become very popular in recent years and location-awareness is a critical step for upcoming applications and communication systems. This paper presents a new localization algorithm through WSNs, which is based on Received Signal Strength (RSS) measurements. Although the localization accuracy obtained is comparable with existing literature...
We report a corrected version of the algorithms to compute ternary projective relations between regions appeared in E. Clementini and R. Billen, "Modeling and computing ternary projective relations between regions," IEEE Transactions on Knowledge and Data Engineering, vol. 18, pp. 799-814, 2006.
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