Path scheduling for multiple mobile actors in wireless sensor network

In wireless sensor network (WSN), energy is the main constraint. In this work we have addressed this issue for single as well as multiple mobile sensor actor network. In this work, we have proposed Rendezvous Point Selection Scheme (RPSS) in which Rendezvous Nodes are selected by set covering problem approach and from that, Rendezvous Points are selected in a way to reduce the tour length. The mobile actors tour is scheduled to pass through those Rendezvous Points as per Travelling Salesman Problem (TSP). We have also proposed novel rendezvous node rotation scheme for fair utilisation of all the nodes. We have compared RPSS with Stationery Actor scheme as well as RD-VT, RD-VT-SMT and WRP-SMT for performance metrics like energy consumption, network lifetime, route length and found the better outcome in all the cases for single actor. We have also applied RPSS for multiple mobile actor case like Multi-Actor Single Depot (MASD) termination and Multi-Actor Multiple Depot (MAMD) termination and observed by extensive simulation that MAMD saves the network energy in optimised way and enhance network lifetime compared to all other schemes.     

A Comprehensive Survey of Various Approaches on Human Fall Detection for Elderly People

With the advancement in the healthcare and medicine sector, now a day’s average life span of humans has increased. Due to an increase in average life expectancy, the demographic of old age people has increased. According to a World Health Organization report, old age people have more chances to get with fall and recurrent fall (World Health Organization in Who global report on falls prevention in older age, 2007). For elder people, human falls may create severe medical issues and injuries too. Because of the ever-growing old age people, there is an urgent requirement for the development of fall detection systems. Fortunately, with the help of advanced biomedical wireless sensor networks, the internet of things, Microelectromechanical sensors, and human–computer interaction it is possible to address this issue of human fall detection. In this research article, we have presented a survey on human fall detection methods and Systems. Human fall detection can be developed using one of the following ways: vision-based techniques, ambient sensor-based techniques, and wearable device-based techniques. In this review article, we have presented a brief review of the above-mentioned methods. Various machine learning methods for fall detection and activity of daily life have been discussed rigorously in this article with available literature.

     

Optimum Trans–Receiver Scheme Using Cross Layer Design for Acoustic Communication

The main objective of this work is to reduce the packet loss due to packet error rate and buffer overflow for under water sensor network. In this work, a system is mapped into various states based on channel condition, buffer space, and available energy level. The set of policies are defined in terms of transmission power level, adaptive modulation scheme, and various transmission rate. We have proposed Optimum Trans–Receiver Scheme (OTRS), in which the problem is formulated as per Markov decision process model and solution is sought in terms of optimum policy identification for an individual state of the system. We have evaluated the performance of OTRS by extensive simulation with existing Adaptive Modulation Power Adaption, Power Adaption with 2 Ary Frequency Shift Keying and Power Adaption with 8 Ary Frequency Shift Keying for various performance matrices like Net Bit Rate and number of packet loss for various state of the system.