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The idea of Smart contracts foresees the possibility of automating contractual clauses using hardware and software tools and devices. One of the main perspectives of their implementation is the automation of interactions such as bets, collaterals, prediction markets, insurances. As blockchain platforms, such as Ethereum, offer very strong guarantees of untampered, deterministic execution, that can be exploited as smart contracts substrate, the problem of how to provide reliable information from the “outside world” into the contracts becomes central. In this article, we propose a system based on a Merkle tree representation of structured documents (such as all XML), with which it is possible to generate compact proofs on the content of web documents. The proofs can then be efficiently checked on-chain by a smart contract, to trigger contract action. We provide an end-to-end proof of concept, applying it to real use case scenarios, which allows us to give an estimate of the costs.

Tokens are digital, transferable and programmable assets and one of the most promising tools offered by blockchains. They could enable a wide range of applications, from down to earth to futuristic. One of the main issues in achieving wide adoption of tokens is onboarding: main platforms require users to deal with specific tools such as wallets, transaction fees, key generation and storage. The most common solution to offer a familiar experience to naive users are custodial intermediaries, which have the important drawback of centralizing the process, and keeping users away from the advantages of self-sovereign assets control. In this paper we present a process for the distribution of digital tokens to end users, exploiting “physical” objects for initial distribution. The process is aimed at making onboarding of users not yet accustomed with blockchain tools and concepts as easy as possible, in a secure and decentralized way.

Tokens are digital, transferable and programmable assets and one of the most promising tools offered by blockchains. They could enable a wide range of applications, from down to earth to futuristic. One of the main issues in achieving wide adoption of tokens is onboarding: main platforms require users to deal with specific tools such as wallets, transaction fees, key generation and storage.The most common solution to offer a familiar experience to naive users are custodial intermediaries, which have the important drawback of centralizing the process, and keeping users away from the intrinsic advantages of blockchains.In this paper we present a process for the distribution of digital tokens to end users, exploiting "physical" objects for initial distribution. The process is aimed at making onboarding of users not yet accustomed with blockchain tools and concepts maximally easy, in a secure and decentralized way.

Promoting the use of public transportation and Intelligent Transport Systems, as well as improving transit accessibility for all citizens, may help in decreasing traffic congestion and air pollution in urban areas. In general, poor information to customers is one of the main issues in public transportation services, which is an important reason for allocating substantial efforts to implement a powerful and easy to use and access information tool. This paper focuses on the design and development of a real time mobility information system for the management of unexpected events, delays and service disruptions concerning public transportation in the city of Milan. Exploiting the information on the status of urban mobility and on the location of citizens, commuters and tourists, the system is able to reschedule in real time their movements. The service proposed stems from the state of the art in the field of travel planners for public transportation, available for Milan. Peculiarly, the authors built a representation of the city transit based on a time-expanded graph that considers the interconnections among all the stops of the rides offered during the day. The structure distinguishes the physical stations and the get on/get off stops of each ride, representing them with two different types of nodes. Such structure allows, with regard to the main focus of the project, to model a wide range of service disruptions, much more meaningful than those possible with approaches currently proposed by transit agencies. One of the most interesting points lies in the expressive capability in describing the different disruptions: with the authors' model it is possible, for instance, to selectively inhibit getting on and/or off at a particular station, avoid specific rides, and model temporary deviations.

The newly introduced car sharing services are an unexploited source of data that could be used to estimate the state of the road network as well as to provide new interesting analysis on urban mobility. In this paper we propose a Knowledge Discovery System that first gathers information from car sharing sites and applications, and then processes it to estimate interesting metrics such as travel time and vehicle flows in the urban areas at different times and in different days. We further argue that the information gathered can be processed in real-time, to estimate instant traffic, and can be exploited to perform deeper analysis, using historical data. Finally, we analyze vehicle availability as a function of time in different zones and show how the results can be applied to travel time estimation, car stockout forecast and multimodal travel planning.