Robust Sensor Networks in Homes via Reactive Channel Hopping

Home area networks (HANs) consisting of wireless sensors have emerged as the enabling technology for important applications such as smart energy and assisted living. A key challenge faced in deploying robust wireless sensor networks (WSNs) for home automation applications is the need to provide long-term, reliable operation in the face of the varied sources of interference found in typical residential settings. To better understand the channel dynamics in these environments, we performed an in-depth empirical study of the performance of HANs in ten real-life apartments. Our empirical study leads to several key insights into designing robust HANs for residential environments. For example, we discover that there is not always a persistently good channel over 24 hours in many apartments; that reliability is strongly correlated across adjacent channels; and that interference does not exhibit cyclic behavior at daily or weekly timescales. Nevertheless, reliability can be maintained through a small number of channel hops. Based on these insights, we propose Adaptive and Robust Channel Hopping (ARCH) protocol, a lightweight receiver-oriented protocol which handles the dynamics of residential environments by reactively channel hopping when channel conditions have degraded. We evaluate our approach through a series of simulations based on real data traces as well as a testbed deployment in real-world apartments. Our results demonstrate that ARCH can reduce the number of packet retransmissions by a median of 42.3% compared to using a single, fixed wireless channel, and can enable up to a 2.2 X improvement in delivery rate on the most unreliable links in our experiment. Due to ARCH\u27s lightweight reactive design, this improvement in reliability is achieved with an average of 6 or fewer channel hops per link per day

2.1.2 Baseband and Link Layers

Recently, low-power wireless networking standards like 802.15.1 (Bluetooth) have driven consumer interest in personal area networks (PANs). These networks are designed for inexpensively connecting low-power devices located within 1 m to 100 m of each other. In this paper, we discuss recent evolutions to the Bluetooth standard, as well as two emerging PAN standards: 802.15.4/ZigBee, and Ultra-Wide Band. We provide a high-level summary of how these standards operate, as well as a brief discussion of what to expect from each technology in the future. See also

Damage Detection on a Full-Scale Highway Sign Structure with a Distributed Wireless Sensor Network

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases

Additional file 8 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 8 Answers according to large et small volume centers. The groups were defined on the median of lung transplants performed in 2017 (n = 28). LTx: lung transplantation

Additional file 5 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 5. Answers to Case 3

Additional file 3 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 3. Answers to Case 1

Additional file 6 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 6. Answers to Case 4

Additional file 2 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 2. Raw anonymized answers of the 99 participant

Additional file 7 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 7. Answers to Case 5

Additional file 4 of Worldwide clinical practices in perioperative antibiotic therapy for lung transplantation

Additional file 4. Answers to Case 2