The emergence of wireless body area network (WBAN) technology has brought hope and dawn to solve the problems of population aging, various chronic diseases, and medical facility shortage. The increasing demand for real-time applications in such networks, stimulates many research activities. Designing such a scheme of critical events while preserving the energy efficiency is a challenging task, due to the dynamic of the network topology, severe constraints on the power supply, and the limited computation power. The design of routing protocols becomes an essential part of WBANs and plays an important role in the communication stacks and has a significant impact on the network performance. In this paper, we briefly introduce WBAN and focus on the analysis of the routing protocol, classify, and compare the advantages and disadvantages of various routing protocols. Lastly, we put forward some problems and suggestions, which provides ideas for the follow-up routing design.

The autonomous parking system is an intelligent technology to park a car into a small space. More and more studies have addressed this issue. However, the planned path in these studies is not smooth enough. Based on Ackermann steering geometry, the car kinematic model is established in this paper, the collision possibility between car body and obstacles in the parking space are analyzed, and then the bound of start point and collision-free space are presented. Based on this, the parking trajectory is planned and Bezier curve is used to smooth the trajectory which is generated on multi arcs of circumference, finally, the generation of continuous curvature path is realized. In the end, we build the environment of the simulation in MATLAB and the Fuzzy PID control method is used to track the trajectory which is planned in advance. The simulation results show that the car can not only avoid the obstacles effectively, but also move smoothly on turning points for using the Bezier curve. The design can meet the continuity of the parking requirements very well.

Wireless body area networks will inevitably bring tremendous convenience to human society in future development, and also enable people to benefit from ubiquitous technological services. However, one of the reasons hindering development is the limited energy of the network nodes. Therefore, the energy consumption in the selection of the next hop must be minimized in multi-hop routing. To solve this problem, this paper proposes an energy efficient routing protocol for reliable data transmission in a wireless body area network. The protocol takes multiple parameters of the network node into account, such as residual energy, transmission efficiency, available bandwidth, and the number of hops to the sink. We construct the maximum benefit function to select the next hop node by normalizing the node parameters, and dynamically select the node with the largest function value as the next hop node. Based on the above work, the proposed method can achieve efficient multi-hop routing transmission of data and improve the reliability of network data transmission. Compared with the priority-based energy-efficient routing algorithm (PERA) and modified new-attempt routing protocol (NEW-ATTEMPT), the simulation results show that the proposed routing protocol uses the maximum benefit function to select the next hop node dynamically, which not only improves the reliability of data transmission, but also significantly improves the energy utilization efficiency of the node and prolongs the network lifetime.

Behaviors are important indicators for assessing the health and well-being of dairy cows. The aim of this study is to develop and validate an ensemble classifier for automatically measuring and distinguishing several behavior patterns of dairy cows from accelerometer data and location data. The ensemble classifier consists of two parts, our new Multi-BP-AdaBoost algorithm and a data fusion method based on D-S evidence theory. We identify seven behavior patterns: feeding, lying, standing, lying down, standing up, normal walking, and active walking. Accuracy, sensitivity, and precision were used to validate classification performance. The Multi-BP-AdaBoost algorithm performed well when identifying lying (92% accuracy, 93% sensitivity, 82% precision), lying down (99%, 82%, 86%), standing up (99%, 74%, 85%), normal walking (97%, 92%, 86%), and active walking (99%, 94%, 89%). Its results were poor for feeding (80%, 52%, 55%) and standing (80%, 46%, 58%), which are difficult to differentiate using a leg-mounted sensor. Position data made it possible to differentiate feeding and standing. The D-S evidence fusion method for combining accelerometer data and location data in classification was used to fuse two pieces of basic behavior-related evidence into a single estimation model. With this addition, the sensitivity and precision of the two difficult behaviors increased by approximately 20 percentage points. In conclusion, the classification results indicate that the ensemble classifier effectively recognizes various behavior patterns in dairy cows. However, further work is needed to study the robustness of the feature and model by increasing the number of cows enrolled in the trial.

The application carrier of wireless body area network (WBAN) is human; due to changes in people’s sports status or physical health and other reasons, the business traffic fluctuates greatly, which requires the network to have good adaptability. In addition, the energy consumption problem is also a key factor restricting the applications of the WBAN. At present, the proposed MAC protocol is not highly adaptive and has low energy efficiency. To solve this problem, this paper proposes an adaptive MAC protocol based on IEEE802.15.6 for WBAN (A-MAC). The protocol sets the data to three priorities according to the type of service; the superframe structure of IEEE802.15.6 is improved and reorganized into four phases: the beacon phase, the contention access phase, the noncontention access phase, and the inactive phase. The length of the contention access phase and the noncontention access phase is adjusted according to the proportion of nodes that generate each priority data. The contention access phase is further divided into three subphases, and the length of the subphase is dynamically adjusted according to the data priority. In the contention access phase, all nodes compete for access channel according to the channel access policy. The random data that competes successfully transmits data directly, and the periodic data that competes successfully transmits data in the allocated time slots of the noncontention access phase. Finally through the simulation of the proposed A-MAC protocol and IEEE 802.15.6 MAC protocol and CA-MAC protocol in network performance which were compared, the results show that in terms of throughput, power consumption, and the network time delay, the network performance using A-mac protocol is better than the network performance using IEEE802.15.6 MAC and CA-MAC protocols.

Aiming to address the issue of multi-user dynamic spectrum access in an opportunistic mode in cognitive radio networks leading to low sum throughput, we propose a multi-user opportunistic spectrum access method based on multi-head self-attention and multi-agent deep reinforcement learning. First, an optimization model for joint channel selection and power control in multi-user systems is constructed based on centralized training with a decentralized execution framework. In the training phase, the decision-making policy is optimized using global information, while in the execution phase, each agent makes decisions according to its observations. Meanwhile, a multi-constraint dynamic proportional reward function is designed to guide the agent in selecting more rational actions by refining the constraints and dynamically adjusting the reward proportion. Furthermore, a multi-head self-attention mechanism is incorporated into the critic network to dynamically allocate attention weights to different users, thereby enhancing the ability of the network to estimate the joint action value. Finally, the proposed method is evaluated in terms of convergence, throughput, and dynamic performance. Simulation results demonstrate that the proposed method significantly improves the sum throughput of secondary users in opportunistic spectrum access.