data fusion wsn using von patel nilay (7 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware -We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results. In this work, I have simulated three methods and two algorithms to get the best posterior data. All the methods were simulated and the result shows how one can reduce error from sensed data of sensors and predict future data based on previous data considering types of error possible in an environment.Books on Demand GmbH, Überseering 33, 22297 Hamburg 76 pp. Englisch.

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Patel NilayNilay Patel is a Lecturer at R.C.Technical Institute and joined academic profession 2016. He has completed post graduation in computer engineering from BVM Engg. College, Anand, Gujarat in 2015 and graduation from CITC, Ch.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results. In this work, I have simulated three methods and two algorithms to get the best posterior data. All the methods were simulated and the result shows how one can reduce error from sensed data of sensors and predict future data based on previous data considering types of error possible in an environment. 76 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results. In this work, I have simulated three methods and two algorithms to get the best posterior data. All the methods were simulated and the result shows how one can reduce error from sensed data of sensors and predict future data based on previous data considering types of error possible in an environment.

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Zustand: New. Print on Demand.