A Collaborative Approach to In-Place Sensor Calibration

By Vladimir Bychkovskiy, S. Megerian, Deborah Estrin, Miodrag Potkonjak. International Symposium on Information Processing in Sensor Networks, 2003

309 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c3617059ca7691f0e801e38c195f2b7ca6ab620e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Mani B. Srivastava
2. Arun Agrahara Somasundara
3. Ramesh Govindan
4. Aditya Ramamoorthy
5. Leana Golubchik
6. Deborah Estrin
7. Sajal K. Das
8. Bhaskar Krishnamachari

In Electrical and Electronic Engineering

1. Ramesh Govindan
2. Mani B. Srivastava
3. Aditya Ramamoorthy
4. Arun Agrahara Somasundara
5. Bhaskar Krishnamachari
6. Deborah Estrin
7. Purushottam Kulkarni
8. Wheeler Ruml

Citations in the corpus

• Mobile Element Scheduling with Dynamic Deadlines (2007, background): “Calibration of sensor nodes is an important problem [18].”
• Sensor faults: Detection methods and prevalence in real-world datasets (2010, background): “[Bychkovskiy et al. 2003], and Balzano and Nowak [Balzano and Nowak 2007] exploit spatial correlation across sensor nodes to develop methods for online sensor calibration that can be used to recover from calibration errors during a deployment, once such an error is detected.”
• The Internet of Things: A Survey from the Data-Centric Perspective (2013, unknown): “In order to reduce such errors, it is possible to either re-calibrate the sensor [25], or perform data-driven cleaning and uncertainty modeling [34].”