Monitoring and Management of Water and Drainage in Smart Cities Using Wireless Sensor Networks
Abstract
This paper aims to present an Internet of Things based solution for
smart and centralized monitoring and managing of water for smart
residential/offices, smart cities, Industries etc. By using this Internet Of
things-based solution we can regulate the usage of water, find out the leakage
and blockage in pipelines, can detect overflow of drainage water. The
information collected can be read by the users on the integrated websites using
their smartphones/laptops device connected to the Internet. Basically, all the
information is gathered from the sensor network which is set using NRF
protocol.
Country : India
1 Potnuru Lavnya
Assistant Professor, Department of Computer Science And Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
IRJIET, Volume 2, Issue 7, September 2018 pp. 24-27
Chang, Wo L. (2015). NIST Big Data
Interoperability Framework: Volume 3, Use Cases and General Requirements. [13]
Szegedy, Christian, Alexander Toshev, and Dumitru Erhan. (2013). “Deep Neural
Networks for Object Detection.” In Advances in Neural Information Processing
Systems, 2553–61.
Erhan, Dumitru, Christian Szegedy,
Alexander Toshev, and Dragomir Anguelov. (2014). “Scalable Object Detection
Using Deep Neural Networks.” In Proceedings of the IEEE Conference on Computer
Vision and Pattern Recognition, 2147–54.
Zeiler, Matthew D, and Rob Fergus.
(2014). “Visualizing and Understanding Convolutional Networks.” In European
Conference on Computer Vision, 818–33.
Sermanet, Pierre et al. (2013).
“Overfeat: Integrated Recognition, Localization and Detection Using
Convolutional Networks.” arXiv preprint arXiv:1312.6229.
Girshick, Ross, Jeff Donahue,
Trevor Darrell, and Jitendra Malik. (2014). “Rich Feature Hierarchies for
Accurate Object Detection and Semantic Segmentation.” In Proceedings of the
IEEE Conference on Computer Vision and Pattern Recognition, 580–87.