GPS-Data from private cycling and public Bikesharing-services on Iota data marketplace - Problem statement: What is the problem you are trying to solve?

In the global context, when people talk about increased traffic volumes in big cities, this means predominantly classic motorised private traffic. It is precisely this type of transport that creates a multitude of problems, risks and challenges for the city. Some of them become very clear from the following figures. Alt-hough the world's cities cover only about 2 percent of the earth's surface, they produce about 80 percent of the world's greenhouse gases. Moreover, accord-ing to a report by the Federal Environment Agency in Germany in 2016, the transportation sector was responsible for around 18 percent of greenhouse gas emissions.
In addition to high pollution levels for city dwellers and the environment, mo-torised private transport triggers also other problems. Traffic noise, high land consumption, an increased risk due to lack of traffic safety, a high dependence on the car as a prerequisite for social participation, as well as a high economic damage caused by traffic jams and lack of movement are further negative con-sequences of motorised individual traffic. Due to urbanization and the result-ing increase in traffic volume, the lack of technological progress and alternative mobility solutions automatically leads to further increases in emissions and en-ergy consumption in the transport sector. The city must therefore create effi-cient transport systems and new mobility solutions that meet the needs of the residents in order to offer them an environment worth living in.
An approach meeting the challenges and creating sustainable solutions for the city and its traffic is summarized under the term Smart Mobility. This is charac-terized by sustainable, innovative and safe transport systems that are linked with their environment using ICT infrastructures. The realization of the over-riding mission of the Smart City, i. e. to increase urban quality of life and com-petitiveness, and to reduce emissions and resource consumption, is accordingly also the goal in the field of action of Smart Mobility.
For some time now there have been new developments in the transport sector based mainly on technological progress. Innovative mobility concepts such as car, ride and bike sharing, electric mobility, autonomous driving, IoT in urban traffic and integrated traffic planning promote the change to the urban traffic of the future. New multimodal mobility services are increasingly linking differ-ent means of transport, whether bus, train, bicycle or car. Contemporary/new mobility apps help the user to determine the fastest route, process the payment or reserve the nearest car sharing car. In addition, the user's increasingly mul-timodal behavior can be optimized by real-time information via the app in such a way that he reaches his destination unerringly and on time, even if there are short-term plan changes. Especially in the bicycle traffic sector are just innu-merable new offers (for example all kinds of Bikesharing suppliers).
But an attractive bicycle traffic requires a high-quality infrastructure. Until now, due to the high cost of onsite data collection, only punctual bicycle traffic anal-yses have been available. Probably the most reliable and most suitable values today are provided by automatic bicycle traffic counting stations that have been permanently installed and have already been set up by many local authorities. A disadvantages here is that the number of survey points is usually clearly way too low for a comprehensive coverage with a better informative value for the entire city. In addition, data is often missing for other parameters such as wait-ing times, route selection or speed of cyclists.
In perspective, this gap can be filled by GPS data, which is now possible by the smartphones, corresponding tracking apps and bikesharing suppliers.
GPS data, as a possibility to map movements in particular and mass data in general, will play an increasingly important role in future for urban and traffic planning. Classic german traffic surveys such as SrV and MiD can thus be sup-plemented by transaction data collected from divergent app providers or pri-vate smartphone owners. This development, however, requires critical scientific monitoring and validation of the resulting data in order to shape the right path towards a high-quality planning basis. This is also necessary because of the weak background of the previous data availability in bicycle traffic planning. The cities of Dresden, Leipzig or Mainz can serve as role models for this, each of them is already taking the first steps towards using GPS data in bicycle traffic planning. These steps are make sense because of the further digitalization of mobility and means of transportation and the resulting growth in the supply of data. In the long term, the use of GPS data offers added value for bicycle traffic planning and thus for sustainable urban and traffic planning.

Market description: What does the market look like? Where would you apply the use-case? Local? Regional? Worldwide?
In addition to new providers such as Obike, Mobike, Yobike and Limebike, es-tablished offers such as the CallaBike of the Deutsche Bahn, or the Vélib' Mét-ropole in Paris are among the general bike sharing offers. As can be seen in the graph, there were only 17 bike sharing providers worldwide in 2005. Ten years later, the number has already increased sixty-fold. In addition, the number of rental bikes in Germany alone has increased more than twentyfold since 2014.

     Figure 1: Number of Bike-Sharing providers worldwide

Due to the enormous increase in bike sharing providers and the number of rental bikes, users are being offered an ever wider and more varied range of services. The increased provision of bicycles that can be borrowed by the public also creates an incentive to switch to environmentally friendly means of trans-portation. Inner city bike sharing offers can therefore make a significant con-tribution to sustainable urban mobility concepts. With the theoretically accom-panying reduction of motorised individual traffic and the provision of multi-modal route chains in connection with public transport for the so-called last mile, central goals of Smart Mobility are adressed. Because the growing number of suppliers and rental bikes in the city increases the potential to emit fewer emissions and to use resources efficiently through the joint use of public bicycle rental systems. The development of the bike-sharing industry is par-ticularly rapid, as new technological innovations are making modern ICT avail-able to suppliers. This makes it possible to provide real-time information on the availability and location of rental bikes.
In addition, the Berlin Senate has set goals for the general promotion of cy-cling. Accordingly, in the next few years there will be:
• Increase in the proportion of cycling to 18-20% of all routes
In Berlin, 1. 5 million journeys are made daily by bicycle.
• Cycling also on longer ways
Cycling should also become so attractive on longer routes that the average distance travelled by bicycle will increase by 25% from 3.7 km to around 4.6 km by 2025.
• Connection with public transport
By providing more and better parking facilities at train and bus stops, the proportion of combined routes is to be increased from the current 3 % to 5%.
• Reduction in the number of accidents
The annual number of cyclists killed in road traffic is to be reduced by 40% by 2025 and the number of injured by 30%.

In addition to the strong positive trend of bicycle traffic in the area of sharing mobility, but also in the objectives of public authorities, the challenges and op-portunities of working with GPS data in bicycle traffic will be mentioned below:
Challenges
• Persons without a suitable terminal device are systematically excluded from the sample.
• Scepticism about data acquisition due to privacy concerns
• Legal requirements, in particular regarding data protection and associated restrictions on the use of data
Chances
• Generation of data in real time
• Filterability according to various criteria
• manageability of cost expenditure
• Replacement of maintenance-intensive counting points
• Obtaining socio-demographic information Fields of application
• Quick overview of cycle traffic volume in main and secondary networks
• Before and after evaluation of measures
• Source-target matrices between polygons
• Waiting times at nodes can be calculated
• Section-fine average speeds
• Routes of individual paths within rough corridors
Theoretically, it is possible to obtain GPS-related data from bike sharing ser-vices or from private cyclists and thus optimize planning worldwide. However, the application example should first move to Berlin, i. e. the local level.

Solution: A detailed overview of how your proposed solution, how IOTA is used in this use-case and what would be needed to achieve this solution.

Alternatives must be found in view of the objective of a Smart City to be sus-tainable and worth living in and the fact that the transport sector in particular accounts for a considerable proportion of air pollution, noise emissions and land consumption. One idea to make the city a better place to live is to promote cycling. However, due to the lack of data, there is little evidence for planners to make inner-city cycling more attractive and to adapt it to current needs. With the new goals of the Berlin Senate, as well as the current trend of bike sharing, new possibilities for urban and traffic planning are emerging. GPS-supported data could create new foundations for sustainable and needs-based bicycle traffic planning. For example, data on private cycling smartphone users could be made available to the planning authorities or shared with providers in coop-eration with municipal institutions.
But in this huge flood of GPS data, which the sensors on the bike produce, there are possible weaknesses and dangers.
Data misuse, poor data protection, system failures, security flaws, data monop-olies, and a sense of supervision and control by governments and corporations due to mass data collection are some negative examples that accompany the increasing flood of digital data. The increasing networking of mobility service providers, vehicles and their users is enabling a smart lifestyle on the one hand and creating a kind of dependency on data on the other, which must be trusted. Cyber-attacks in particular could increase in the future, since cities or even pri-vate economic enterprises have stored the users data on central data servers. This creates new potential dangers for the cities, which could increasingly be targets for cyber-attacks. Any company or city that stores and processes data through networked sensors can become the victim of such an attack. In the city of the future, for example, a cyberattack could provide all electronic-charging points with malware so that not a single car can be charged. It would also be possible to influence the digitized and networked traffic management of a city, which would result in a mega-congestion.
This is where Iota comes in..

IOTA's public distributed ledger architecture provides free data integrity that resolves the security concerns associated with data trading. In addition, this design means that the network stays completely decentralized. The feature of the developed Iota Data marketplace is to have a truly decentralized data mar-ket to open the data monopolies that currently limit data control to a few com-panies. Masked Authenticated Messaging (MAM) can be used to offer GPS data via the tangle on the data marketplace. Given its characteristics, MAM meets an important need in industries where integrity and privacy meet. Since most ma-jor bike sharing providers already work via GPS, they would only have to offer it (if legally permitted) via the data marketplace. Private persons can, in order to remain completely decentralized, modify their own Raspberry Pi in such a way that it records GPS to later pack the motion profile onto the data marketplace via the tangle.
So my idea is to upload recorded GPS data from cycling, either from individuals or from bike-sharing companies, to the Iota Market-place so that cities and planning offices can purchase it from it with MIOTA. This provides the following advantages:
• GPS data, which is already available at bike sharing providers, can be further used and made available for on-demand and long-term city-traffic plan-ning.
• The storage, transmission of data functions, unlike in existing systems, completely decentralized and thus protected from becoming so called “glass citizens”.
• Private individuals can trade their GPS data on the Iota Data marketplace themselves, thus creating added value for this data.
The following challenges are on the agenda:
• Legal situation with data protection and data transfer to third parties
• Previously unknown planning basis for planners
• New economic sectors are emerging, cities need a rethink by becoming ac-tive as investors on the Data Marketplace.
• Purely technical aspect of how real-time motion profiles can be offered and sold on the Tangle and on the data marketplace.
• Instructions for private users to record the data with a homemade private sensor and not to use a central app where you lose power over your data.