International Journal of Sensors Wireless Communications and Control - Volume 2, Issue 1, 2012

Home automation has been an active and intense area of research since the times when electricity was made available widely. Home automation comprises a number of sub-areas, among which is home monitoring, and home surveillance. Interest in home monitoring has just begun to emerge as a number of sensors become available, exhibiting ever increasing sophistication and offered capabilities. This paper reports on the development and experimentation of a novel extensible platform for the monitoring of the home environment, which allows complex event processing by collecting measurements from sensor that are deployed in a home environment as a stream of events, and using knowledge engineering techniques for detecting the events of interest to be communicated to the user's mobile phone, allowing thus a user to monitor its home from remote locations. Experiences with the platform are also presented in the paper.

In this paper, we argue that sensors provide a better understanding of geographic events. They produce observations that reflect the natural events taking place at a particular location. The essential part of deriving information about geographic events from sensor observations is to formalize the relations between them. In this spirit, we develop an ontology to capture the relations between weather events and properties observed by sensors. A case study is investigated to illustrate how blizzard events can be formally represented in relation to a set of atmospheric properties observed by a weather station. Using the ontological structures, we define and implement rules to reason about blizzard events from hourly weather observations. We use the historical weather records from the Canadian Climate Archives database to evaluate our approach. The result includes an interactive timeline illustrating the events. The approach is evaluated in terms of reasoning and querying support against a local use.

This paper presents a novel approach to combine, process and enrich data from heterogeneous sensor networks, and, further, to semantically annotate the observations of the sensed world thus obtained and publish them on the future Semantic Sensor Web. The processing and systematic annotation of sensor data of diverse nature obtained from an ever growing number of different sources that are beginning to shape the Sensor Web is a challenging endeavour. Nevertheless, a similar challenge is inherent to the activity of Human-Machine Interface designers. In this field the SCXML language, based on the concept of Harel statecharts, is being proposed by the W3C as a central element in the design of multimodal interaction managers, which have to deal with information in different communication modalities, integrating and interpreting the user's input, and coordinating the output among them. We propose extending the use of SCXML to deal also with sensor information, as this language has the capability to combine and process this information as it does with interaction information. SCXML can also coordinate external tools (based on RDF, OGC-SWE's O&M and OWL) to generate semantic annotations of the knowledge obtained, shareable across applications. This approach can pave the way to develop rich context-aware applications. We illustrate the discussion with a smart-car scenario that we have developed, and present the main implementation details.

In cases when the information being collected and processed originates by a multi-sensor system, one has to be aware of the impact of the approaches followed in designing the overall system behavior. Typically, there are many steps involved in processing sensory information, from the time a real-world event takes place until the information that describes it and captures its semantics is stored and is available for further exploitation. It this paper we analyze and discuss the options available in the design phase while we underline their respective strengths and weaknesses. The main contribution of the paper lies in the analysis of the factors that affect the behavior and performance of an information system responsible for fusing and integrating sensory information. The main components that constitute such systems are presented in depth, while every choice and the respective effects are discussed in an organized and complete manner.

The deceptive jamming method is one of the effective ways to jam SAR, and in order to implement deceptive jamming, not only should we estimate the main parameters such as frequency, pulse width, PRF, etc, but also need to locate the jammed SAR. This paper is mainly talking about the effect of SAR platform position error on the deceptive jamming. The accuracy of the jammed SAR position required for deception jamming is deduced according to the given precision of deceptive target position. The bistatic location method is adopted in this paper to locate SAR platform and the accuracy of this location method is also analyzed. Besides, an improved new jamming method which calls for azimuth and elevation angle measurement only is introduced and its angular error effect on deceptive jamming is discussed. The location difficulty can be reduced with this improved jamming method which makes it more feasible to put into practice.

The data fusion can come down to a process that combines the state vectors from different sources to obtain a more accurate result. Compare to the achieved results that depend on single source, the method has gained an improved performance and reduced the computational complexity and bandwidth of transmission as well. This paper makes use of Probabilistic Data Association (PDA) algorithm and Joint Probabilistic Data Association (JPDA) algorithm to track the Multi-target for each local sensor in a clutter environment. Furthermore, a method based on statistical double-threshold association algorithm and covariance-weighted fusion algorithm is proposed in this paper. Meanwhile, the simulation result shows that the performance has been improved significantly in multi-sensor and multi-target tracking progress with the proposed method in the paper.