Towards Efficient Sensor Placement for Industrial Wireless Sensor Network

Industrial Wireless Sensor Network (IWSN) is the recent emergence in wireless technologies that facilitate industrial applications. IWSN constructs a reliable and self-responding industrial system using interconnected intelligent sensors. These sensors continuously monitor and analyze the industrial process to evoke its best performance. Since the sensors are resource-constrained and communicate wirelessly, the excess sensor placement utilizes more energy and also affects the environment. Thus, sensors need to use efficiently to minimize their network traffic and energy utilization. In this paper, we proposed a vertex coloring based optimal sensor placement to determine the minimal sensor requirement for an efficient network

Broadcast Scheduling Problem in TDMA Ad Hoc Networks using Immune Genetic Algorithm

In this paper, a new efficient immune genetic algorithm (IGA) is proposed for broadcast scheduling problem in TDMA Ad hoc network. Broadcast scheduling is a primary issue in wireless ad hoc networks. The objective of a broadcast schedule is to deliver a message from a given source to all other nodes in a minimum amount of time. Broadcast scheduling avoids packet collisions by allowing the nodes transmission that does not make interference of a time division multiple access (TDMA) ad hoc network. It also improves the transmission utilization by assigning one transmission time slot to one or more non-conflicting nodes such a way that every node transmits at least once in each TDMA frame. An optimum transmission schedule could minimize the length of a TDMA frame while maximizing the total number of transmissions. The aim of this paper is to increase the number of transmissions in fixed Ad hoc network with time division multiple access (TDMA) method, with in a reduced time slot. The results of IGA are compared to the recently reported algorithms. The simulation result indicates that IGA performs better even for a larger network

Physical activity patterns and gestational diabetes outcomes – The wings project

AbstractObjectiveTo compare physical activity (PA) patterns in pregnant woman with and without gestational diabetes (GDM) and to assess the effects of an exercise intervention on change in PA patterns, blood glucose levels and pregnancy outcomes in GDM women.MethodsFor the first objective, PA patterns were studied in 795 pregnant women with and without GDM. For the second objective, the Women in India with Gestational Diabetes Strategy-Model of Care (WINGS-MOC) intervention were evaluated in 151 women out of 189 with GDM. PA was assessed using a validated questionnaire and a pedometer. Changes in PA patterns, glycemic parameters and neonatal outcomes were evaluated.ResultsOverall, only 10% of pregnant women performed recommended levels of PA. Women with GDM were significantly more sedentary compared to those without GDM (86.2 vs. 61.2%, p<0.001). After the MOC was implemented in women with GDM, there was a significant improvement in PA and a decrease in sedentary behaviour amongst women (before MOC, moderate activity: 15.2%, sedentary: 84.8% vs. after MOC-moderate: 26.5%, sedentary: 73.5%; p<0.001), and an increase in their daily step count from 2206/day to 2476/day (p<0.001). Fasting 1 and 2-h postprandial glucose values significantly decreased (p<0.001 for all). Sedentary behaviour was associated with a fourfold higher risk (p=0.02), and recreational walking with 70% decreased risk, of adverse neonatal outcomes (p=0.04) after adjusting for potential confounders.ConclusionsPA levels are inadequate amongst this group of pregnant women studied i.e. those with and without GDM. However, a low-cost, culturally appropriate MOC can bring about significant improvements in PA in women with GDM. These changes are associated with improved glycemic control and reduction in adverse neonatal outcomes

Towards Efficient Sensor Placement for Industrial Wireless Sensor Network

Industrial Wireless Sensor Network (IWSN) is the recent emergence in wireless technologies that facilitate industrial applications. IWSN constructs a reliable and self-responding industrial system using interconnected intelligent sensors. These sensors continuously monitor and analyze the industrial process to evoke its best performance. Since the sensors are resource-constrained and communicate wirelessly, the excess sensor placement utilizes more energy and also affects the environment. Thus, sensors need to use efficiently to minimize their network traffic and energy utilization. In this paper, we proposed a vertex coloring based optimal sensor placement to determine the minimal sensor requirement for an efficient network