Investigation of Architecture and Essential Technologies of Wireless Sensor Network

This paper introduces the architecture of wireless sensor networks, presents a cross-layer network management and control mechanism. The key technologies, such as Medium Access Control (MAC) and wireless routing protocols are discussed and compared. A proposal of applying the simple IEEE 802 MAC protocol into the wireless sensor network is introduced. In addition, in order to improve the system capacity, a multi-channel strategy for the sensor nodes is presented for decreasing the blocking probability and suppressing the accessing time delay. It is concluded that there are still a number of problems to be solved, including decreasing power consumption, improving capacity and avoiding access collision, to promote the successful commercial application of wireless sensor network.

The Influence of Quantum Technology on the Development of Metrology and Measuring Science

In the new century, quantum technology has developed rapidly and has been applied in many fields. As an important aspect of the aerospace science, metrology and measuring science is a field which is influenced by the quantum technology dramatically. The new generation of the International System of Units will be redefined on the basis of the quantum theory. More and more new sensing techniques are developed taking into account quantum principles. In this paper, the influence of quantum technology on metrology and measuring science is introduced.

Research Needs and Applications of Machine Learning｡ｪPredicting Logistics Stress by Machine Learning

Machine learning is the use of computers to learn the intrinsic laws and information contained in data through algorithms to gain new experience and knowledge,in order to improve the intelligence of computers,so that they can make decisions similar to those made by humans when faced with problems.With the development of various industries,the amount of data has increased and the efficiency of data processing and analysis has become more demanding,a series of machine learning algorithms have emerged.Machine learning algorithms are essentially steps and processes that apply a large number of statistical principles to solve optimisation problems.Appropriate machine learning algorithms can be used to solve practical problems more efficiently for a wide range of model requirements.This paper presents the interim state of a dynamic disruption management software solution for logistics,using machine learning methods to study the extent to which stress is predicted based on physiological and subjective parameters,to prevent physical and mental stress on workers in the logistics industry,to maintain their health,to make them more optimistic and better able to adapt to their work,and to facilitate more accurate deployment of human resources by companies according to the real-time requirements of the logistics industry.

Current Status of Intelligent Space

Latest advances in network sensor technology and state of the art of mobile robotics and artificial intelligence research can be applied to develop autonomous and distributed monitoring systems. Intelligent Space （iSpace） is an environmental system, which is able to support human in informative and physical ways. iSpace observing the space with distributed sensors, extracts useful information from the obtained data and provides various services to users. This means that essential functions of iSpace are ＂observation＂, ＂recognition＂ and ＂actuation.＂ In this paper, we focus on the observation function of iSpace. And we describe observation systems to get information of both human and mobile agents in the space to show new results.

ANFIS-based Sensor Fusion System of Sit-to-stand for Elderly People Assistive Device Protocols

This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several experiments were carried out using a motion capture system（VICON） and inertial sensors to identify the human posture during the sit-to-stand motion.The EJAD uses only two inertial measurement units（IMUs） fused through an adaptive neuro-fuzzy inference systems（ANFIS） algorithm to imitate the real motion of the caregiver.The EJAD consists of two main parts,a robot arm and an active walker.The robot arm is a 2-degree-of-freedom（2-DOF） planar manipulator.In addition,a back support with a passive joint is used to support the patient s back.The IMUs on the leg and trunk of the patient are used to compensate for and adapt to the EJAD system motion depending on the obtained patient posture.The ANFIS algorithm is used to train the fuzzy system that converts the IMUs signals to the right posture of the patient.A control scheme is proposed to control the system motion based on practical measurements taken from the experiments.A computer simulation showed a relatively good performance of the EJAD in assisting the patient.