ABSTRACT
Sensor networks that collect data from the environment can be utilized in the development of different context-aware applications bringing in sight the need for data collection, management and distribution. Boards with microcontrollers are gaining on acceptance and popularity in the latest years mainly for educational and research purposes. Utilizing the information available via sensors connected to these platforms requires the presence of adequate infrastructure for the management of the sensor system, in order to retrieve information and control its use. In this work, we present the prototype of our sensor management system SensoMan that manages a collection of sensors spread in the environment connected to specific boards. The proposed system can be extended with more sensors and combined with different applications for the efficient use of the sensor data in context-aware applications. In this paper we present the architecture of SensoMan and its main modules.
- Abowd, G. D., Dey, A. K., Brown, P. J., Davies, N., Smith, M., and Steggles, P. 1999. Towards a better understanding of context and context-awareness. Handheld and ubiquitous computing, 304--307. Springer Berlin Heidelberg. Google ScholarDigital Library
- Achilleos, A. P., and Kapitsaki, G. M 2014. Enabling Cross-Platform Mobile Application Development: A Context-Aware Middleware. In Proceedings of the Web Information Systems Engineering conference, (Thessaloniki, Greece) WISE '14. Springer International Publishing. 304--318. DOI= 10.1007/978-3-319-11746-1_22.Google Scholar
- Alamri, A. Ansari, W. S., Hassan, M. M., Hossain, M. S., Alelaiwi, A. and Hossain, M. A., 2013. A Survey on Sensor-Cloud: Architecture, Applications, and Approaches, International Journal of Distributed Sensor Networks, 3, Article ID 917923.Google ScholarCross Ref
- Cleary, J. G., and Trigg, L. E. 1995. K*: An instance-based learner using an entropic distance measure. In Proceedings of the 12th International Conference on Machine learning. Vol. 5, 108--114.Google Scholar
- Dohr, A., Modre-Opsrian, R., Drobics, M., Hayn, D., and Schreier, G. 2010. The internet of things for ambient assisted living. In Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations (ITNG), 804--809. DOI= 10.1109/ITNG.2010.104. Google ScholarDigital Library
- Kapitsaki, G. M., Kateros, D. A., Prezerakos, G. N., and Venieris, I. S. 2009. Model-driven development of composite context-aware web applications. Information and Software technology, 51(8), 1244--1260. Google ScholarDigital Library
- Kaufmann, B. and Buechley, L. 2010. Amarino: a toolkit for the rapid prototyping of mobile ubiquitous computing. In Proceedings of the 12th international conference on Human computer interaction with mobile devices and services, 291--298, ACM. Google ScholarDigital Library
- Laoudias, C., Constantinou, G., Constantinides, M., Nicolaou, S., Zeinalipour-Yazti, D., and Panayiotou, C. G. 2012. The airplace indoor positioning platform for android smartphones. In Proceedings of the IEEE 13th International Conference on Mobile Data Management, (MDM 12), 312--315). Google ScholarDigital Library
- Moraru, A., Pesko, M., Porcius, M., Fortuna, C. and Mladenic, D. 2010. Using machine learning on sensor data. In Proceedings of the 2010 32nd International Conference on Information Technology Interfaces (ITI), 573,578.Google Scholar
- Perera, C., Zaslavsky, A., Christen, P., and Georgakopoulos, D. 2014. Context aware computing for the internet of things: A survey. Communications Surveys & Tutorials, IEEE, 16(1), 414--454.Google Scholar
- Rajkumar, R. R., Lee, I., Sha, L., & Stankovic, J. (2010, June). Cyber-physical systems: the next computing revolution. In Proceedings of the 47th Design Automation Conference (pp. 731--736). ACM. Google ScholarDigital Library
- Ramli, K. N., Joret, A. and Saad. N. H. 2014. Development of Home Energy Management System Using Arduino. In Proceedings of the Second International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE 14). The Society of Digital Information and Wireless Communication.Google Scholar
- Truong, H. L., and Dustdar, S. 2009. A survey on context-aware web service systems. International Journal of Web Information Systems, 5(1).Google Scholar
Index Terms
- SensoMan: Remote management of context sensors
Recommendations
Vehicle monitoring using internet of things
IML '17: Proceedings of the 1st International Conference on Internet of Things and Machine LearningWireless Sensor Networks is one of the newly emerging technologies to assist Internet of Things (IoT) related applications. In this paper, a wireless based vehicular sensor network system is proposed to address the commonly occurring problems such as ...
Localized sensor management for multi-target tracking in wireless sensor networks
For a multi-hop wireless sensor network, the limited sensing and communication resources give rise to distinct challenges to the task of tracking mobile targets, which is traditionally treated primarily from the data fusion perspective. This paper ...
Sensor management
Wireless sensor networksSensors are deployed in a sensor network for the purpose of providing data about environmental phenomena to the sink node(s). As not all sensors may be able to transmit their data directly to the sink(s), sensors must also route other sensors' data. ...
Comments