New types of networking II – Using indirect knowledgeNew types of networking II – Using indirect knowledge https://www.widas.in/wp-content/themes/corpus/images/empty/thumbnail.jpg 150 150 manu.mukundan manu.mukundan https://secure.gravatar.com/avatar/c332174d6f39134704a6d0e9b94482a7?s=96&d=mm&r=g
New Types of Networking II - Using Indirect Knowledge
In the previous part, various situations were used to show how the technical networking of everyday objects, which are often viewed in isolation, can develop in the future. In most cases, however, the systems involved only acted among themselves, i.e. without reference to the huge amounts of data generated by the most diverse actors every day.
These include movement profiles of people and machines, surfing behavior on the Internet, price and offer developments, consumer behavior and transaction data, communication profiles and much more. Often the metadata are at least as interesting as the actual information. The big challenge is to structure and evaluate these data volumes. Currently, this is often still done to create added value for third parties. However, this data can also be evaluated to make everyday life easier for the individual or to protect him or her from unpopularity. Some examples of concepts in modern mobility can be
- Vehicle Traffic Flow Analysis 1 – Congestion Avoidance and Route Planning:In-car navigation devices are able to make route adjustments based on traffic messages. The technique used is the evaluation of TMC messages. These are transmitted digitally in the inaudible VHF frequency range and are not necessarily as up-to-date as appropriate due to their centralized collection and management. In addition, the transmission technology offers only a very limited data throughput. Instead of using stationary cameras or induction loops in the roadway, it would be conceivable without problems to record the movement information of the individual vehicles. Coupled with data from navigation systems and statistical evaluations of traffic behavior, depending on the day of the week and time of day, it would in many cases be possible to make much more precise statements about alternative routes and the associated time savings in avoiding traffic jams much earlier.
The motion profiles of the individual vehicles on which such a statement is based could be recorded, transmitted and received either by the vehicle itself or by smartphones carried along. The advantages of this system would be, among others, the quality and decentralized collection of the data as well as the timely and highly available evaluation and interpretation. Challenges are certainly first and foremost the need for a high-performance mobile data network and the costs of data evaluation and transmission. With correspondingly advanced anonymization and aggregation methods, however, this data collection does not represent a significant intrusion into the privacy of the individual road user.
- Traffic Flow Analysis 2 – Parking Guidance Systems: The well-known problematic parking situation in city centers is often met today with parking guidance systems. Here, the parking garages and parking lots report the available parking spaces, a display system shows the sum of these in the direction of travel. The actual gain of information is often only very small: either there are still enough parking spaces or not at all. As an aid for the individual car driver to find a parking space near his destination, they are often of limited use. What is missing is the dimension of the number of vehicles in front of the driver on the way to this parking place. Thus, these guidance systems only provide information about the actual situation at the current time, but they do not provide any information about the expected situation upon arrival. Similar to the previous example, the number, position and route of all vehicles in the vicinity can be used to make a statement about the probability of finding a parking space at the desired destination. In a second step, the overall system could offer alternatives that are in close proximity to the destination or recommend parking spaces in the peripheral areas, taking into account information about routes and schedules. Since parking near the center is often the more expensive alternative, a proposal for the parking space with the lowest total costs can be made, taking into account the fare and number of passengers.
In this scenario we explicitly assume a symmetrical distribution of information, i.e. local knowledge of locals about “secret paths”, “insider tips” etc. is not taken into consideration.
To find out how the growing networking of people and machines with future technologies and concepts can make everyday life even easier, read the next section “New types of networking III – Facebook