Abstract-Over the last decade, embedded sensing systems have been successfully deployed in a range of application areas, from education and science to military, healthcare and industry. These systems are becoming more robust, capable and widely adopted. However, every particular applications requires complex integration work and therefore technical expertise, effort and time which prevents users from creating small tactical, ad-hoc applications using sensor networks. These limitations are already addressed by implementing service oriented architecture in the wireless sensor networks. In addition to that, many real time applications are very time critical and demand richer set of applications. To address this issue, we propose an extended service oriented architecture (ESOA) that provides customizable sensor network, consolidates services and manages applications.

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In order to reduce the greenhouse gas emission and limit the rise in global temperature, the trend in automotive industry is changing rapidly and most of the manufacturers are moving towards the electrification of vehicles. Computational intelligence and machine learning play a very important role in the field of electric vehicles (EVs) due to the necessity of automatic control in battery charging and port accessibility. Due to the limited ranges

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