NS
N. Salheb
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2 records found
1
This study presents a methodology to convert from the most dominant 3D city model standard in 3D GIS to BIM. Namely, CityGML to IFC. IFC is chosen because it is the common open standard to exchange data in the BIM world. For the aim of this study, the two standards are divided into 5 comparable sub-parts; Semantics, Geometry, Geographical coordinates, Topology, and Encoding. The characteristics of each of these sub-parts are studied and a theoretical conversion method is proposed for it from the first standard to the other. This is done by performing a semantic and geometrical mapping between the two standards, converting the georeferencing from Global to local, converting the encoding that the two standards use from XML to STEP, deciding which topological relations are to be retained, and providing a basic implementation that is created using Python to combine the above tasks. The work presented in this thesis can provide a foundation for future work in converting CityGML to IFC. It provides an insight into the relationship between the two standards and a methodology for the conversion from one to the other, and the process of developing software to perform such conversion. This is done in a way that can be extended for future specific needs.
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This study presents a methodology to convert from the most dominant 3D city model standard in 3D GIS to BIM. Namely, CityGML to IFC. IFC is chosen because it is the common open standard to exchange data in the BIM world. For the aim of this study, the two standards are divided into 5 comparable sub-parts; Semantics, Geometry, Geographical coordinates, Topology, and Encoding. The characteristics of each of these sub-parts are studied and a theoretical conversion method is proposed for it from the first standard to the other. This is done by performing a semantic and geometrical mapping between the two standards, converting the georeferencing from Global to local, converting the encoding that the two standards use from XML to STEP, deciding which topological relations are to be retained, and providing a basic implementation that is created using Python to combine the above tasks. The work presented in this thesis can provide a foundation for future work in converting CityGML to IFC. It provides an insight into the relationship between the two standards and a methodology for the conversion from one to the other, and the process of developing software to perform such conversion. This is done in a way that can be extended for future specific needs.
Raising awareness of citizens by interactively providing environmental data
Pilot of a static sensor network in Delft
Student report
(2017)
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Niek Bebelaar, Cathelijne Kleijwegt, Roeland Meulmeester, Gina Michailidou, Nebras Salheb, Noortje Vaissier, Stefan van der Spek, Wilko Quak, Teun Verkerk
This synthesis project is focused on implementing an Internet of Things (IoT) network to measure environmental data in the city of Delft. This network consists of sensor platforms that are placed in the urban environment. Each sensor platform is mounted on fixed locations and it is not moved during the measurement time. The aim is to raise community’s environmental awareness to improve the quality of the environment.
Recent developments in technology made it possible to fabricate small, efficient, and reliable sensors boards which are the base of these sensors platforms and making them efficient and reliable. Sensor boards like Arduino, Raspberry Pi, and LoPy are some examples of these small sensor boards. In this project, the LoPy is used which is a sensor board that is equipped with Bluetooth Low Energy, Wifi and a LoRa radio. This last one is a communication technology that makes longer communication distances possible.
The sensor network measures four different environmental indicators that will be distributed to the public: temperature, humidity, noise and air quality. The network then communicates via LoRa this data to one centralized server where the data is stored, processed and sent back to the citizens. This data is made publicly accessible to academia, citizens and the stakeholders alike. The network is also made interactive, people who pass by can interact with the sensors and request specific environmental data in real time.
The sensor network has been build and deployed in the city. During the uptime of the network it succeeded to provide the data to the citizens via the feedback mechanisms: a website with a dashboard and an automated twitter account. Local differences have been measured with temperature and humidity sensors. With regard to the noise sensor and air quality sensors no definitive conclusions could be drawn.
...
Recent developments in technology made it possible to fabricate small, efficient, and reliable sensors boards which are the base of these sensors platforms and making them efficient and reliable. Sensor boards like Arduino, Raspberry Pi, and LoPy are some examples of these small sensor boards. In this project, the LoPy is used which is a sensor board that is equipped with Bluetooth Low Energy, Wifi and a LoRa radio. This last one is a communication technology that makes longer communication distances possible.
The sensor network measures four different environmental indicators that will be distributed to the public: temperature, humidity, noise and air quality. The network then communicates via LoRa this data to one centralized server where the data is stored, processed and sent back to the citizens. This data is made publicly accessible to academia, citizens and the stakeholders alike. The network is also made interactive, people who pass by can interact with the sensors and request specific environmental data in real time.
The sensor network has been build and deployed in the city. During the uptime of the network it succeeded to provide the data to the citizens via the feedback mechanisms: a website with a dashboard and an automated twitter account. Local differences have been measured with temperature and humidity sensors. With regard to the noise sensor and air quality sensors no definitive conclusions could be drawn.
...
This synthesis project is focused on implementing an Internet of Things (IoT) network to measure environmental data in the city of Delft. This network consists of sensor platforms that are placed in the urban environment. Each sensor platform is mounted on fixed locations and it is not moved during the measurement time. The aim is to raise community’s environmental awareness to improve the quality of the environment.
Recent developments in technology made it possible to fabricate small, efficient, and reliable sensors boards which are the base of these sensors platforms and making them efficient and reliable. Sensor boards like Arduino, Raspberry Pi, and LoPy are some examples of these small sensor boards. In this project, the LoPy is used which is a sensor board that is equipped with Bluetooth Low Energy, Wifi and a LoRa radio. This last one is a communication technology that makes longer communication distances possible.
The sensor network measures four different environmental indicators that will be distributed to the public: temperature, humidity, noise and air quality. The network then communicates via LoRa this data to one centralized server where the data is stored, processed and sent back to the citizens. This data is made publicly accessible to academia, citizens and the stakeholders alike. The network is also made interactive, people who pass by can interact with the sensors and request specific environmental data in real time.
The sensor network has been build and deployed in the city. During the uptime of the network it succeeded to provide the data to the citizens via the feedback mechanisms: a website with a dashboard and an automated twitter account. Local differences have been measured with temperature and humidity sensors. With regard to the noise sensor and air quality sensors no definitive conclusions could be drawn.
Recent developments in technology made it possible to fabricate small, efficient, and reliable sensors boards which are the base of these sensors platforms and making them efficient and reliable. Sensor boards like Arduino, Raspberry Pi, and LoPy are some examples of these small sensor boards. In this project, the LoPy is used which is a sensor board that is equipped with Bluetooth Low Energy, Wifi and a LoRa radio. This last one is a communication technology that makes longer communication distances possible.
The sensor network measures four different environmental indicators that will be distributed to the public: temperature, humidity, noise and air quality. The network then communicates via LoRa this data to one centralized server where the data is stored, processed and sent back to the citizens. This data is made publicly accessible to academia, citizens and the stakeholders alike. The network is also made interactive, people who pass by can interact with the sensors and request specific environmental data in real time.
The sensor network has been build and deployed in the city. During the uptime of the network it succeeded to provide the data to the citizens via the feedback mechanisms: a website with a dashboard and an automated twitter account. Local differences have been measured with temperature and humidity sensors. With regard to the noise sensor and air quality sensors no definitive conclusions could be drawn.