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Guru Subramanyam Kanakadandi


Rel. Stefano D'Ambrosio, Sundaram Kannan. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2021


The wireless sensor network consists of wireless devices for monitoring environment and physical conditions of diesel engines. The main advantage of wireless network is a flexible network and can easily adapt changes. The main parameters that are considered in Wireless sensor technology is temperature, pressure, speed, and the pollution level. Wireless sensors technology helps diesel engine to enhance fuel consumption in injection system by controlling of all fuel injector in engine to optimised level depending upon the speed and acceleration of the vehicle. These wireless technologies can also use for controlling harmful gas that exist from exhaust to atmosphere. The main application of wireless sensor technology application is air pollution monitoring which is exhaust gas. A weak network and isolated knowledge is used existed in the production line in a complicated discreet manufacturing system, leading to sluggish input and low usage ratio, hindering the building of business intelligence. To solve these problems, a study of unpredictable variables and demands of the sensor network was conducted, suggested hierarchical topological architecture methods and the implementation strategy for the dynamic industrial internet of the objects, and developed a big data analysis and a network-based framework of safety defence. The weight of each assessment index was determined by the analytical hierarchy method that defined the intelligence assessment structure and model. In order to confirm the viability of the process, a real production scene was also chosen. The intelligence degree was measured and assessed in quantitative as well as qualitative respects, focusing on both subjective and analytical considerations.

Relators: Stefano D'Ambrosio, Sundaram Kannan
Academic year: 2021/22
Publication type: Electronic
Number of Pages: 102
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo)
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Aziende collaboratrici: Ashok Leyland Limited
URI: http://webthesis.biblio.polito.it/id/eprint/20774
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