International Journal of Sensor Networks and Data Communications

Background: With the advancement of wireless technology and in-build tiny electronics increase the connection between systems and humans. Development of wireless systems based on the internet of things (IOT) revolutionizes the industrial sector and transforms the traditional lifestyle into a high tech lifestyle. The wireless sensor network (WSN) is the central element of the wireless system based on IOT because it contains a number of sensor nodes interconnected with the help of wireless channels and its capability to monitor the real world objects. Being a part of wireless systems based on IOT, in particular can be employed in multiple domains such as health, agriculture and industrial domain. The wireless system based on IOT increases the instant access of data from the surrounding environment and improves the quality of human life. Hence, the attention of this review is to shine a light on WSN and architecture classification of wireless systems based on IOT. In spite of this, we highlight the challenges associated with integration of IOT to WSN.

Background: In the present research work we have examined the biosensing capabilities of one-dimensional photonic crystal with defect suitable for detection and sensing of malaria inflection by means of investigating samples containing red blood cells. This theoretical work is based on transfer matrix formulation in addition to MATLAB software under normal incidence condition due to several difficulties associated with oblique incidence. We have evaluated the performance by taking random cavity thicknesses of 1000 nm, 2200 nm, 3000 nm and 5000 nm to estimate the cavity thickness suitable for optimum performance of the proposed biosensing design. The optimization of cavity is one of the most necessary requirements because it decides the minimum volume requirement of the blood sample for getting results of high accuracy. Moreover sensing and detection capabilities of the proposed design has been evaluated by examining the sensitivity, figure of merit and quality factor values of the design corresponding to optimum cavity thickness.

Background DaS S gives a remote sensor network multi-sensor information data combination plot utilizing the Bayesian technique and Insect Province Improvement innovation, and carries out the arnd low-power versatile grouping and various leveled computation given by it. The outcomes demonstrated the way that the proposed calculation can really lessen the utilization of energy and save more energy, in this manner expanding the existence of the general organization. Zhai HS proposed a new multi-sensor information examination calculation in light of unscented Kalman channel and wavelet change.