A study of the RF characteristics for wireless sensor deployment in building environment

In this paper, The radio Frequency (RF) Monitoring and Measurement of the Environmental Research Institute (ERI) located in Cork city will be monitored and analyzed in both the Zigbee (2.44 GHz) and the industrial, scientific and medical (ISM 433 MHz). The main objective of this survey is to confirm what the noise and interferences threat signals exist in these bands. It was agreed that the surveys would be carried out in 5 different rooms and areas that are candidates for the Wireless Sensors deployments. Based on the carried on study, A Zigbee standard Wireless Sensor Network (WSN) will be developed employing a number of motes for sensing number of signals like temperature, light and humidity beside the RSSI and battery voltage monitoring. Such system will be used later on to control and improve indoor building climate at reduced costs, remove the need for cabling and both installation and operational costs are significantly reduced.

Walking in hospital is associated with a shorter length of stay in older medical inpatients

Evidence suggests that inactivity during a hospital stay is associated with poor health outcomes in older medical inpatients. We aimed to estimate the associations of average daily step-count (walking) in hospital with physical performance and length of stay in this population. Medical in-patients aged ⩾65 years, premorbidly mobile, with an anticipated length of stay ⩾3 d, were recruited. Measurements included average daily step-count, continuously recorded until discharge, or for a maximum of 7 d (Stepwatch Activity Monitor); co-morbidity (CIRS-G); frailty (SHARE F-I); and baseline and end-of-study physical performance (short physical performance battery). Linear regression models were used to estimate associations between step-count and end-of-study physical performance or length of stay. Length of stay was log transformed in the first model, and step-count was log transformed in both models. Similar models were used to adjust for potential confounders. Data from 154 patients (mean 77 years, SD 7.4) were analysed. The unadjusted models estimated for each unit increase in the natural log of stepcount, the natural log of length of stay decreased by 0.18 (95% CI −0.27 to −0.09). After adjustment of potential confounders, while the strength of the inverse association was attenuated, it remained significant (βlog(steps) = −0.15, 95%CI −0.26 to −0.03). The back-transformed result suggested that a 50% increase in step-count was associated with a 6% shorter length of stay. There was no apparent association between step-count and end-of-study physical performance once baseline physical performance was adjusted for. The results indicate that step-count is independently associated with hospital length of stay, and merits further investigation.