Energy-efficient Urban Sensing
Immanuel Schweizer(Author)
Cuvillier Verlag
1st Edition
Published on 18. January 2013
Book
168 pages
978-3-95404-328-6 (ISBN)
Description
Since 2008, more than 50% of all people worldwide are living in urban areas. The urban population is expected to grow from 3.5 billion to 5 billion over the next 20 years. Population density, waste, poverty, mobility, and air quality are just some examples of challenges faced in urban areas today and even more in the future.
A solution proposed today is known as smart city. The main idea is to use information and communication technology to provide a kind of 'real-time data layer' for cities. This will increase the transparency and efficiency for all stakeholders (e.g., citizens, industry, commerce, and government). In order to attempt to provide such a real-time data layer, wireless sensor networks are identified as the key technology. They are supposed to offer a cheap and easy solution for large-scale deployments. In addition, wireless communication reduces the need for further infrastructure.
We identified three key challenges in applying urban sensor networks: (i) deployment, (ii) standards and generic solutions, and (iii) energy. This work focuses on new approaches tackling the energy challenge and how real-world systems can be built.
More details
Edition
1., Aufl.
Language
English
Dimensions
Height: 210 mm
Width: 148 mm
Thickness: 10 mm
Weight
226 gr
ISBN-13
978-3-95404-328-6 (9783954043286)
Schweitzer Classification
Other editions
Additional editions

Person
Dr. Immanuel Schweizer is currently heading the Smart Urban Networks area of the Telecooperation Department at Technische Universität Darmstadt. He started his work at the department as a research associate in 2009 after finishing his master's degree in computer science. He received his Doctorate from Technische Universität Darmstadt in 2012 for his work on energy-efficient wireless sensor networks with an emphasis on urban applications. His group is working on energy-efficient and resilient data and service networks and on improving data quality and quantity using virtual sensors.