CONTEXT In 2016, an estimated 54.5% of the world’s population lived in urban settlements. By 2030, urban areas are projected to house 60% of people globally and one in every three people will live in cities with at least half a million inhabitants. The complexity of this urbanisation it will therefore have to be governed by new and innovative methods: the starting point is the data collection to large area and punctual data respect to many parameters that describe the current population and its urban and road area infrastructures status. These data must be shared between the government bodies in charge of planning, realization and maintenance of urban environment. One of the main components to establish this database is
3dimensional modelling: the ability to detect the urban environment with appropriate sensors, describe and represent the geometry with specific process software is a fundamental element not only for the urban planning, but also for the accurate cataloguing of the urbana and road infrastructures and for the evaluation of their state. Understanding a street scene is a major issue in the field of automatic information processing. Indeed, a street scene may be composed of a variety of elements, making its processing challenging. Still components (buildings, trees, road, pavements, posts, etc.) as well as mobile entities (vehicles, people, thrash bin) may be encountered, and each street scene is a unique combination of common/unexpected elements. This challenging field could bring important application in various fields such as road safety, autonomous vehicles, video surveillance, traffic simulation or public domain smart maintenance. Accurate and timely updated 3dimensional building modelling is a critical component in environmental and modern urban information systems.Remote sensing technologies provide an innovative means for monitoring, synthesis and modeling urban environments. Recent progresses of very-high resolution, hyperspectral, LiDAR, and UAV remote sensing techniques, together with traditional medium-resolution and coarse-resolution imagery, make a comprehensive understanding and modelling of urban environments possible.
PROBLEM STATEMENT Infrastructure, especially the road network, keeps Europe running: ensures mobility - in the neighbourhood, municipality, the region or beyond and its quality affects almost everybody in daily life. The European Road Network consists of a multiplex of networks that range from the Trans European Network (TEN), to national (motorway and trunk) roads, to regional roads and, finally, to local roads.
Lack of maintenance: chronic underfunding and lack of maintenance can very quickly jeopardise this huge asset, which has been built at great expense and effort in the last decades. Roads like buildings need to be maintained to avoid very costly actions. According to an ERF estimation the value of reconstruction of the entire European road network is worth over € 8,000 billion.
Fatalities: In 2011, the European Commission unveiled its 4th Road Safety Action Programme, which set a highly ambitious target of reducing fatalities across the EU by 50% by 2020 compared to 2010.
At the same time, there is the problem of developing smart cities, increasingly populated cities, which will have to face the challenge of sustainability and quality of life and which will require new methods of resource management, infrastructure maintenance and surveillance of the urban fabric. This can only be achieved through improved availability and management of data that must be finalized to make decisions to manage and evaluate in order to trigger a circle of continuous improvement.
The results originating from the market research and the technical overview suggested working on a business idea based on an offer of an integrated data collection service, automatic or semi-automatic processing and sharing of information with the customer (road operator or smart cities administration/company ready for use with or without dedicated software.
In general, the offer is designed to meet the needs in the Road Sector:
1) The Cadastre of the road/road network
2) Monitoring of the state of health and comfort of the road network, of the urban and road infrastructures
3)The development of assisted /autonomous driving
4) The development of the smart cities
GOALS AND SOLUTION The objective of the project is to develop a technology that help road concessionaires and urban administrations to make roads safer and maintained, and cities smarter and more citizen-oriented through better administration of urban and road infrastructures, and resource management technological and economic.
This can be achieved through the collect of the data with Scanfly is a Lidar payload not only for UAV designed and produced in Italy by 3D Target that It allows for accurate 3D mapping also from land vehicles. But the data must be become information so with robust post-processing software, based on intelligent algorithms and deep learning, 3D target will offer meaningful information is extracted and elaborate to enable road management companies and municipalities administration to manage the infrastructures and make the roads and the cities smarter and safe.
