• Energy Research

The performance of a Wireless Body Area Network (WBAN) depends on the Quality of Service (QoS) and energy efficiency. The traffic generated by WBAN is heterogeneous in nature, and consists of both periodic and emergency events. One crucial challenge in designing a WBAN Medium Access Control (MAC) protocol is guaranteeing high-reliability transmission while satisfying diverse QoS requirements. Therefore, this paper proposes a QoS-aware MAC protocol named the Adaptive MAC (ADT-MAC) that accommodates dynamic medical traffic by addressing emergency and periodic traffic requirements. ADT-MAC utilizes a hybrid and adaptive superframe structure based on the IEEE 802.15.6 standard. Additionally, an M/M/1 queuing algorithm with a non-preemptive priority is modeled using SimEvents in MATLAB to validate the packet delay of the priority queues. The proposed ADT-MAC protocol is simulated using Castalia and OMNeT++ to evaluate its performance against state-of-the-art MAC protocols. Simulation findings reveal that ADT-MAC achieves lower packet delay, higher PDR, and increased network throughput while reducing energy consumption compared to its benchmarks. Furthermore, the result of packet delay from priority queues validates the accuracy of the proposed ADT-MAC and queueing algorithm. The two-fold simulation approach using Castalia and SimEvents demonstrated that the packet delay for each priority level remains below the 125 ms threshold set by the IEEE 802.15.6 specifications.

Wearable power supply devices and systems are important necessities for the emerging textile electronic applications. Current energy supply devices usually need more space than the device they power, and are often based on rigid and bulky materials, making them difficult to wear. Fabric-based batteries without any rigid electrical components are therefore ideal candidates to solve the problem of powering these devices. Printing technologies have greater potential in manufacturing lightweight and low-cost batteries with high areal capacity and generating high voltages which are crucial for electronic textile (e-textile) applications. In this review, we present various printing techniques, and battery chemistries applied for smart fabrics, and give a comparison between them in terms of their potential to power the next generation of electronic textiles. Series combinations of many of these printed and distributed battery cells, using electrically conducting threads, have demonstrated their ability to power different electronic devices with a specific voltage and current requirements. Therefore, the present review summarizes the chemistries and material components of several flexible and textile-based batteries, and provides an outlook for the future development of fabric-based printed batteries for wearable and electronic textile applications with enhanced level of DC voltage and current for long periods of time.

The function of the heart electrostimulator is explained in this paper through the hardware realization of electrical circuit proposed by company „Medtronic”, Detail explanation of main components of the realized pacemaker has been given and signals generated by the pacemaker were recorded with oscilloscope. The nead for use of electrostimulators is explained through the transmition of electric potential through the cardiac muscle and disorders that occur during this transmition.

Lack of parking spaces in cities makes modern life in cities more difficult. The constant increase in the number of people in cities is followed by an increase of vehicles on streets which results in decrees of unoccupied parking spaces. Also, drivers are making illegal use of parking spaces reserved for people with disabilities, and because of that people with disabilities cannot rely on using these parking spaces. This paper presents a solution that is based on the validation of drivers that park their vehicles in parking spaces for people with disabilities. By detection of parking sensor that parking space is occupied and by validation of user through user mobile app after scanning QR code, the described system verifies validation of user and in case that user is not allowed to park appropriate service is notified.

The dynamic nature of energy harvesting rate, arising because of ever changing weather conditions, raises new concerns in energy harvesting based wireless sensor networks (EH-WSNs). Therefore, this drives the development of energy aware EH solutions. Formerly, many Medium Access Control (MAC) protocols have been developed for EH-WSNs. However, optimizing MAC protocol performance by incorporating predicted future energy intake is relatively new in EH-WSNs. Furthermore, existing MAC protocols do not fully harness the high harvested energy to perform aggressively despite the availability of sufficient energy resources. Therefore, a prediction-based adaptive duty cycle (PADC) MAC protocol has been proposed, called PADC-MAC, that incorporates current and future harvested energy information using the mathematical formulation to improve network performance. Furthermore, a machine learning model, namely nonlinear autoregressive (NAR) neural network, is employed that achieves good prediction accuracy under dynamic harvesting scenarios. As a result, it enables the receiver node to perform aggressively better when there is sufficient inflow of incoming harvesting energy. In addition, PADC-MAC uses a self-adaptation technique that reduces energy consumption. The performance of PADC-MAC is evaluated using GreenCastalia in terms of packet delay, network throughput, packet delivery ratio, energy consumption per bit, receiver energy consumption, and total network energy consumption using realistic harvesting data for 96 consecutive hours under dynamic solar harvesting conditions. The simulation results show that PADC-MAC provides lower average packet delay of the highest priority packets and all packets, energy consumption per bit, and total energy consumption by more than 10.7%, 7.8%, 81%, and 76.4%, respectively when compared to three state-of-the-art protocols for EH-WSNs.