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Mobility and logistics activities could be supported effectively if the mobile users may know the best path to destination and the loading and unloading paths by means of navigators based on the current traffic and weather conditions. Also, personal data as well user preferences should be considered by the navigators to generate effective recommendations. However, not all the relevant data may be known in a precise way since they often derive from statistical information, as well as knowing all the real time information is not always feasible due to the high cost of the sensing systems. Moreover, we don't have simple mathematical models able to generate fast right recommendations, as required in the rapidly evolving scenarios featuring the activities of walking and driving people. For this reason, the paper aims at illustrating how fuzzy logic may be used for computing measurements and perceptions by qualitative rules and to generate timely recommendations helpful to mobile users. These recommendations will consider the environmental conditions in real time, the current personal constraints and the preferences expressed in the past by the users. The paper not only proposes the methodology, but also illustrates how a Ruby on Rails server provided with a proper JQMobile interface may offer such location intelligence services taking also advantage from the information coming from social networks. A Flash Builder version to save the RoR server time and to improve privacy is also illustrated.
Date of Conference: 22-24 June 2012