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TC4.5 - MicroApplication for suggestions

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Test Case Title

 TC4.5 - MicroApplication for suggestions

Goal
  • request via API and App to have suggestion about what is around to me, taking into account my past requests and profile, (as city users)
  • request via API and App to have a hints from the Personal Assistant on the basis of my profile and past my experience on the system (as City Users)
  • program Suggestion and Hints provided by the personal Assistant according to rules (as city Operator)
  • connection via HTTPS/HTTP

Prerequisites

Using a PC or Mobile with a web browser. Using a web or mobile application to test this feature. WEB application has to provide GPS coordinates. The Suggestions can be requested directly in PULL. While the Assistance can be provided in PUSH according to some rules. To create fake rules and provide you example you need to: (i) download and install on Android the App called “Toscana dove cosa”, (ii) get registered and communicate to us your email used for registration. So that we can include you in the testing team and send to you actions and hints, dedicated to your testing.

The following functionalities are available only for specific Snap4city users with specific privileges.

Expected successful result

Obtaining suggestions and seeing how they work. They can also work by using simple REST CALL.

Obtaining assistance hints. In this case, the solution has to learn your behaviour. The testing can also show you how the rules for the Personal Assistance are defined, and provided, how the results are monitored, etc.

Steps

  

 

Please note that some of the following links could be accessible only for registered users.

Among the services of the Advanced Smart City API there are two mechanisms for sending hints to the users: the Suggester

  • Are based on the information collected by the user profile (identified anonymously by the mobile phone ID) plus additional information about the user behaviour, accepted suggestions, past and current GPS locations.
  • Produce suggestions and hints according to the data available. Even few anonymous data can be exploited to produce valid suggestions and hints even if not very complete and smart.

Provide suggestion to a specific user for services, events and other entities around a specific position

https://screcommender.km4city.org/SmartCityRecommender/?action=recommend&user=3043b85d23d6f4879e1765c2c2e431cbc71d393065af06b03486ba4a04642b5b&profile=student&language=en&latitude=43.7727&longitude=11.2532&distance=1&version=1 

The result is also a JSON similar to that reported in the following,

 

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