Towards Human Stress and Activity Recognition: A Review and a First Approach Based on Low-Cost Wearables

Detecting stress when performing physical activities is an interesting field that has received relatively little research interest to date. In this paper, we took a first step towards redressing this, through a comprehensive review and the design of a low-cost body area network (BAN) made of a set of wearables that allow physiological signals and human movements to be captured simultaneously. We used four different wearables: OpenBCI and three other open-hardware custom-made designs that communicate via bluetooth low energy (BLE) to an external computer—following the edge-computingconcept—hosting applications for data synchronization and storage. We obtained a large number of physiological signals (electroencephalography (EEG), electrocardiography (ECG), breathing rate (BR), electrodermal activity (EDA), and skin temperature (ST)) with which we analyzed internal states in general, but with a focus on stress. The findings show the reliability and feasibility of the proposed body area network (BAN) according to battery lifetime (greater than 15 h), packet loss rate (0% for our custom-made designs), and signal quality (signal-noise ratio (SNR) of 9.8 dB for the ECG circuit, and 61.6 dB for the EDA). Moreover, we conducted a preliminary experiment to gauge the main ECG features for stress detection during rest.

Microcontroller-Based Lead-Acid Battery Balancing System for Electric Vehicle Applications

In application of lead-acid batteries for electrical vehicle applications, 48 V of four 12 V batteries in a series configuration are required. However, the battery stack is repeatedly charged and discharged during operation. Hence, differences in charging and discharging speeds may result in a different state-of-charge of battery cells. Without proper protection, it may cause an excessive discharge that leads to premature degradation of the battery. Therefore, a lead-acid battery requires a battery management system to extend the battery lifetime. Following the LTC3305 balancing scheme, the battery balancing circuit with auxiliary storage can employ an imbalance detection algorithm for sequential battery. It happens by comparing the voltage of a battery on the stack and the auxiliary storage. In this paper, we have replaced the function of LTC3305 by a NUCLEO F767ZI microcontroller, so that the balancing process, the battery voltage, the drawn current to or from the auxiliary battery, and the surrounding temperature can be fully monitored. The prototype of a microcontroller-based lead-acid battery balancing system for electrical vehicle application has been fabricated successfully in this work. The batteries voltage monitoring, the auxiliary battery drawn current monitoring, the overcurrent and overheat protection system of this device has also successfully built. Based on the experimental results, the largest voltage imbalance is between battery 1 and battery 2 with a voltage imbalance of 180 mV. This value is still higher than the target of voltage imbalance that must be lower than 12.5 mV. The balancing process for the timer mode operation is faster 1.5 times compared to the continuous mode operation. However, there were no overcurrent or overtemperature occurred during the balancing process for both timer mode and continuous mode operation. Furthermore, refinement of this device prototype is required in the future to improve the performance significantly.

FaceBit

The COVID-19 pandemic has dramatically increased the use of face masks across the world. Aside from physical distancing, they are among the most effective protection for healthcare workers and the general population. Face masks are passive devices, however, and cannot alert the user in case of improper fit or mask degradation. Additionally, face masks are optimally positioned to give unique insight into some personal health metrics. Recognizing this limitation and opportunity, we present FaceBit: an open-source research platform for smart face mask applications. FaceBit's design was informed by needfinding studies with a cohort of health professionals. Small and easily secured into any face mask, FaceBit is accompanied by a mobile application that provides a user interface and facilitates research. It monitors heart rate without skin contact via ballistocardiography, respiration rate via temperature changes, and mask-fit and wear time from pressure signals, all on-device with an energy-efficient runtime system. FaceBit can harvest energy from breathing, motion, or sunlight to supplement its tiny primary cell battery that alone delivers a battery lifetime of 11 days or more. FaceBit empowers the mobile computing community to jumpstart research in smart face mask sensing and inference, and provides a sustainable, convenient form factor for health management, applicable to COVID-19 frontline workers and beyond.

Performance Analysis of Secure Elements for IoT

New protocol stacks provide wireless IPv6 connectivity down to low power embedded IoT devices. From a security point of view, this leads to high exposure of such IoT devices. Consequently, even though they are highly resource-constrained, these IoT devices need to fulfil similar security requirements as conventional computers. The challenge is to leverage well-known cybersecurity techniques for such devices without dramatically increasing power consumption (and therefore reducing battery lifetime) or the cost regarding memory sizes and required processor performance. Various semiconductor vendors have introduced dedicated hardware devices, so-called secure elements that address these cryptographic challenges. Secure elements provide tamper-resistant memory and hardware-accelerated cryptographic computation support. Moreover, they can be used for mutual authentication with peers, ensuring data integrity and confidentiality, and various other security-related use cases. Nevertheless, publicly available performance figures on energy consumption and execution times are scarce. This paper introduces the concept of secure elements and provides a measurement setup for selected individual cryptographic primitives and a DTLS handshake over CoAPs in a realistic use case. Consequently, the paper presents quantitative results for the performance of five secure elements. Based on these results, we discuss the characteristics of the individual secure elements and supply developers with the information needed to select a suitable secure element for a specific application.

An Effective Control for Lead-Acid Performance Enhancement in a Hybrid Battery-Supercapacitor System Used in Transport Vehicles

Modern vehicles have increased functioning necessities, including more energy/power, storage for recovering decelerating energy, start/stop criteria, etc. However, lead-acid batteries (LABs) possess a shorter lifetime than lithium-ion and supercapacitors energy storage systems. The use of LABs harms the operation of transport vehicles. Therefore, this research paper pursues to improve the operating performance of LABs in association with their lifetime. Integrated LAB and supercapacitor improve the battery lifetime and efficiently provide for transport vehicles’ operational requirements and implementation. The study adopts an active-parallel topology approach to hybridise LAB and supercapacitor. A fully active-parallel topology structure comprises two DC-to-DC conversion systems. LAB and supercapacitor are connected as inputs to these converters to allow effective and easy control of energy and power. A cascaded proportional integrate-derivative (PID) controller regulates the DC-to-DC converters to manage the charge/release of combined energy storage systems. The PID controls energy share between energy storage systems, hence assisting in enhancing LAB lifetime. The study presents two case studies, including the sole battery application using different capacities, and the second, by combining a battery with a supercapacitor of varying capacity sizes. A simulation software tool, Matlab/Simulink, is used to develop the model and validate the results of the system. The simulation outcomes show that the battery alone cannot serve the typical transport vehicle (TV) requirements. The battery and output voltage of the DC-to-DC conversion systems stabilises at 12 V, which ensures consistent DC bus link voltage. The energy storage (battery) state-of-charge (SoC) is reserved in the range of 90% to 96%, thus increasing its lifespan by 8200 cycles. The battery is kept at the desired voltage to supply all connected loads on the DC bus at rated device voltage. The fully active topology model for hybrid LAB and supercapacitor provides a complete degree of control for individual energy sources, thus allowing the energy storage systems to operate as they prefer.

An Efficient and Reliable Algorithm for Wireless Sensor Network

In wireless sensor networks (WSN), flooding increases the reliability in terms of successful transmission of a packet with higher overhead. The flooding consumes the resources of the network quickly, especially in sensor networks, mobile ad-hoc networks, and vehicular ad-hoc networks in terms of the lifetime of the node, lifetime of the network, and battery lifetime, etc. This paper aims to develop an efficient and reliable protocol by using multicasting and unicasting to overcome the issue of higher overhead due to flooding. Unicasting is used when the desired destination is at a minimum distance to avoid an extra overhead and increases the efficiency of the network in terms of overhead and energy because unicasting is favorable where the distance is minimum. Similarly, multicasting is used when the desired destination is at maximum distance and increases the network’s reliability in terms of throughput. The results are implemented in the Department of Computer Science, Bacha Khan University Charsadda (BKUC), Pakistan, as well as in the Network Simulator-2 (NS-2). The results are compared with benchmark schemes such as PUMA and ERASCA, and based on the results, the performance of the proposed approach is improved in terms of overhead, throughput, and packet delivery fraction by avoiding flooding.

Genetic Algorithm-Based Multi-Hop Routing to Improve the Lifetime of Wireless Sensor Networks

Wireless sensor networks are known for their monitoring and tracking application-specific operations. These operations diversely demand improvement in existing strategies and their parameters. One key parameter is energy usage during operations. Energy plays a vital role in each application, as the wireless sensor networks lack battery lifetime and energy resources. So, there is a need for an optimized and efficient routing method with regard to energy consumption in wireless sensor networks. For multi-hop routing, the genetic algorithm serves as a robust algorithm with diverse optimized routing plans to improve the lifespan for large-scale wireless sensor networks. In this paper, the genetic algorithm provides the optimized routes for data operations and improves the lifetime of wireless sensor networks by saving energy. The performance of the genetic algorithm is compared with the TEEN algorithm.

Calendar Degradation and Self-Discharge Occurring During Short- and Long-Term Storage of NMC Based Lithium-Ion Batteries

Idling periods are a major part of the Lithium-ion battery operation. Due to parasitic reactions, the battery capacity is decreasing and self-discharge occurs over time. Thus, in order to predict the battery lifetime and optimize its operation, it is required to capture this behavior. In this study, two different storage periods of 2 and 6 months were investigated and used to develop and validate models dedicated to reversible and irreversible capacity loss. It has been observed that while for the shorter storage period, the self-discharge rate does not change significantly, for the longer storage period it decreased during aging. Moreover, the degradation rates vary significantly for various time scales at low temperature, while at medium and high temperatures they are matching closely for 2- and 6-months periodic storage.

Accelerated Battery Lifetime Simulations Using Adaptive Inter-Cycle Extrapolation Algorithm

We propose algorithms to speed up physics-based battery lifetime simulations by one to two orders of magnitude compared to the state-of-the-art. First, we propose a reformulation of the Single Particle Model with side reactions to remove algebraic equations and hence reduce stiffness, with 3x speed-up in simulation time (intra-cycle reformulation). Second, we introduce an algorithm that makes use of the difference between the `fast' timescale of battery cycling and the `slow' timescale of battery degradation by adaptively selecting and simulating representative cycles, skipping other cycles, and hence requires fewer cycle simulations to simulate the entire lifetime (adaptive inter-cycle extrapolation). This algorithm is demonstrated with a specific degradation mechanism but can be applied to various models of aging phenomena. In the particular case study considered, simulations of the entire lifetime are performed in under 5 seconds. This opens the possibility for much faster and more accurate model development, testing, and comparison with experimental data.