Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Outcomes of seizures, status epilepticus, and EEG findings in critically ill patient with COVID-19

OBJECTIVE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has a myriad of neurological manifestations and its effects on the nervous system are increasingly recognized. Seizures and status epilepticus (SE) are reported in the novel coronavirus disease (COVID-19), both new onset and worsening of existing epilepsy; however, the exact prevalence is still unknown. The primary aim of this study was to correlate the presence of seizures, status epilepticus, and specific critical care EEG patterns with patient functional outcomes in those with COVID-19. METHODS: This is a retrospective, multicenter cohort of COVID-19-positive patients in Southeast Michigan who underwent electroencephalography (EEG) from March 12th through May 15th, 2020. All patients had confirmed nasopharyngeal PCR for COVID-19. EEG patterns were characterized per 2012 ACNS critical care EEG terminology. Clinical and demographic variables were collected by medical chart review. Outcomes were divided into recovered, recovered with disability, or deceased. RESULTS: Out of the total of 4100 patients hospitalized with COVID-19, 110 patients (2.68%) had EEG during their hospitalization; 64% were male, 67% were African American with mean age of 63 years (range 20-87). The majority (70%) had severe COVID-19, were intubated, or had multi-organ failure. The median length of hospitalization was 26.5 days (IQR = 15 to 44 days). During hospitalization, of the patients who had EEG, 21.8% had new-onset seizure including 7% with status epilepticus, majority (87.5%) with no prior epilepsy. Forty-nine (45%) patients died in the hospital, 46 (42%) recovered but maintained a disability and 15 (14%) recovered without a disability. The EEG findings associated with outcomes were background slowing/attenuation (recovered 60% vs recovered/disabled 96% vs died 96%, p \u3c 0.001) and normal (recovered 27% vs recovered/disabled 0% vs died 1%, p \u3c 0.001). However, these findings were no longer significant after adjusting for severity of COVID-19. CONCLUSION: In this large multicenter study from Southeast Michigan, one of the early COVID-19 epicenters in the US, none of the EEG findings were significantly correlated with outcomes in critically ill COVID-19 patients. Although seizures and status epilepticus could be encountered in COVID-19, the occurrence did not correlate with the patients\u27 functional outcome

ISI-TR-2005-602b

Abstract — Distributed time synchronization is an important part of a sensor network where sensing and actuation must be coordinated across multiple nodes. Several time synchronization protocol that maximize accuracy and energy conservation have been developed, including FTSP, TPSN, and RBS. All of these assume nearly instantaneous wireless communication between sensor nodes; each of them work well in today’s RF-based sensor networks. We are just beginning to explore underwater sensor networks where communication is primarily via acoustic telemetry. With acoustic communication, where the propagation speed is nearly five orders of magnitude slower than RF, assumptions about rapid communication are incorrect and new approaches to time synchronization are required. We present Time Synchronization for High Latency (TSHL), designed assuming such high latency propagation. We show through analysis and simulation that it achieves precise time synchronization with minimal energy cost. Although at very short distances existing protocols are adequate, TSHL shows twice the accuracy at 500m, demonstrating the need to model both clock skew and propagation latency. I

Contention analysis of MAC protocols that count

The key aspect in the design of any contention-based medium access control (MAC) protocol is the mechanism to measure and resolve simultaneous contention. Generally, terrestrial wireless MACs can only observe success or collision of a con-tention attempt through carrier sense. An implicit estimate of the number of contenders occurs through repeated ob-servation and changing back-o contention window. Recent work in underwater MAC protocols suggest there it is pos-sible to directly count the number of contenders by exploit-ing the spatio-temporal uncertainty inherent to high-latency underwater acoustic medium. Prior work has shown how to use counting in underwater MACs, and how to optimize con-tention windows in radio MACs. In this paper, we quantify bounds to convergence time for MAC protocols employing exact contender counting. We show that perfect counting al-lows contention to converge quickly, independent of network density, with an asymptotic limit of 3.6 contention rounds on average. We conrm this analysis with simulation of a specic underwater MAC protocol, and suggest the oppor-tunity for the results to generalize for any radio-based MACs that estimate contenders

Time Synchronization for High Latency Acoustic Networks

Distributed time synchronization is an important part of a sensor network where sensing and actuation must be coordinated across multiple nodes. Several time synchronization protocol that maximize accuracy and energy conservation have been developed, including FTSP, TPSN, and RBS. All of these assume nearly instantaneous wireless communication between sensor nodes; each of them work well in today’s RF-based sensor networks. We are just beginning to explore underwater sensor networks where communication is primarily via acoustic telemetry. With acoustic communication, where the propagation speed is nearly five orders of magnitude slower than RF, assumptions about rapid communication are incorrect and new approaches to time synchronization are required. We present Time Synchronization for High Latency (TSHL), designed assuming such high latency propagation. We show through analysis and simulation that it achieves precise time synchronization with minimal energy cost. Although at very short distances existing protocols are adequate, TSHL shows twice the accuracy at 500m, demonstrating the need to model both clock skew and propagation latency.