| 1. |
- Carlos, Perez Penichet, et al.
(författare)
-
Augmenting IoT networks with backscatter-enabled passive sensor tags
- 2016
-
Ingår i: Proceedings of the 3rd Workshop on Hot Topics in Wireless. - New York, NY, USA : ACM. - 9781450342513 ; , s. 23-27
-
Konferensbidrag (refereegranskat)abstract
- The sensing modalities available in an Internet-of-Things (IoT) network are usually fixed before deployment, when the operator selects a suitable IoT platform. Retrofitting a deployment with additional sensors can be cumbersome, because it requires either modifying the deployed hardware or adding new devices that then have to be maintained. In this paper, we present our vision and work towards passive sensor tags: battery-free devices that allow to augment existing IoT deployments with additional sensing capabilities without the need to modify the existing deployment. Our passive sensor tags use backscatter transmissions to communicate with the deployed network. Crucially, they do this in a way that is compatible with the deployed network's radio protocol, and without the need for additional infrastructure. We present an FPGA-based prototype of a passive sensor tag that can communicate with unmodified 802.15.4 IoT devices. Our initial experiments with the prototype support the feasibility of our approach. We also lay out the next steps towards fully realizing the vision of passive sensor tags.
|
|
| 2. |
|
|
| 3. |
- Hassanzadeh, Navid, et al.
(författare)
-
Do Sensor Networks need Mobile MAC Protocols?
- 2012
-
Ingår i: CONET'12: Proceedings of the 3rd Workshop on Networks of Cooperating Objects in conjunction with CPS Week.
-
Konferensbidrag (refereegranskat)
|
|
| 4. |
- Hassanzadeh, N., et al.
(författare)
-
Efficient mobile data collection with mobile collect
- 2012
-
Ingår i: Proceedings - IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2012. - : IEEE. - 9780769547077 ; , s. 25-32
-
Konferensbidrag (refereegranskat)abstract
- The main task of most deployed wireless sensor networks is data collection. While a number of solutions have been designed for static networks, there are currently no widely used data collection algorithms for mobile sensor networks. In this paper, we concentrate on scenarios where many nodes, both data sources and sinks, move along a certain track in one direction, a scenario that is common in sports events. Rather than designing a new protocol from scratch, we extend an existing data collection protocol with lightweight mechanisms to make it efficient for mobility. Our extensive simulations and results in a test bed that includes mobile robots demonstrate that our solution is able to achieve high packet delivery rates at low energy consumption. For our target scenario, our solution more than doubles packet delivery rates when the network is sparse. Our solution also works well in scenarios with a higher degree of mobility where nodes move according to a more demanding random waypoint model.
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
- Hermans, Frederik, et al.
(författare)
-
A Lightweight Approach to Online Detection and Classification of Interference in 802.15.4-based Sensor Networks
- 2012
-
Ingår i: ACM SIGBED Review. - : Association for Computing Machinery (ACM). - 1551-3688. ; 9:3, s. 11-20
-
Tidskriftsartikel (refereegranskat)abstract
- With a rapidly increasing number of devices sharing access to the 2.4 GHz ISM band, interference becomes a serious problem for 802.15.4-based, low-power sensor networks. Consequently, interference mitigation strategies are becoming commonplace. In this paper, we consider the step that precedes interference mitigation: interference detection. We have performed extensive measurements to characterize how different types of interferers affect individual 802.15.4 packets. From these measurements, we define a set of features which we use to train a neural network to classify the source of interference of a corrupted packet. Our approach is sufficiently lightweight for online use in a resource constrained sensor network. It does not require additional hardware, nor does it use active spectrum sensing or probing packets. Instead, all information about interferers is gathered from inspecting corrupted packets that are received during the sensor network’s regular operation. Even without considering a history of earlier packets, our approach reaches a mean classification accuracy of 79.8%, with per interferer accuracies of64.9% for WiFi, 82.6% for Bluetooth, 72.1% for microwave ovens, and 99.6% for packets that are corrupted due to insufficient signal strength.
|
|
| 9. |
|
|
| 10. |
- Hermans, Frederik, et al.
(författare)
-
FOCUS : Robust Visual Codes for Everyone
- 2016. - 28
-
Ingår i: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys 2016). - New York, NY, USA : ACM. - 9781450342698 ; , s. 319-332
-
Konferensbidrag (refereegranskat)abstract
- Visual codes are used to embed digital data in physical objects, or they are shown in video sequences to transfer data over screen/camera links. Existing codes either carry limited data to make them robust against a range of channel conditions (e.g., low camera quality or long distances), or they support a high data capacity but only work over a narrow range of channel conditions. We present Focus, a new code design that does not require this explicit trade-off between code capacity and the reader’s channel quality. Instead,Focus builds on concepts from OFDM to encode data at different levels of spatial detail. This enables each reader to decode as much data from a code as its channel quality allows. We build a prototype of Focus devices and evaluate it experimentally. Our results show that Focus gracefully adapts to the reader’s channel, and that it provides a significant performance improvement over recently proposed designs, including Strata and PixNet.
|
|
