Long-range Capability Research Articles

Efficient diagnostic classification of diverse pathologies through contextual eye movement data analysis with a novel hybrid architecture

The analysis of eye movements has proven valuable for understanding brain function and the neuropathology of various disorders. This research aims to utilize eye movement data analysis as a screening tool for differentiation between eight different groups of pathologies, including scholar, neurologic, and postural disorders. Leveraging a dataset from 20 clinical centers, all employing AIDEAL and REMOBI eye movement technologies this study extends prior research by considering a multi-annotation setting, incorporating information from recordings from saccade and vergence eye movement tests, and using contextual information (e.g. target signals and latency of the eye movement relative to the target and confidence level of the quality of eye movement recording) to improve accuracy while reducing noise interference. Additionally, we introduce a novel hybrid architecture that combines the weight-sharing feature of convolution layers with the long-range capabilities of the transformer architecture to improve model efficiency and reduce the computation cost by a factor of 3.36, while still being competitive in terms of macro F1 score. Evaluated on two diverse datasets, our method demonstrates promising results, the most powerful discrimination being Attention & Neurologic; with a macro F1 score of up to 78.8%; disorder. The results indicate the effectiveness of our approach in classifying eye movement data from different pathologies and different clinical centers accurately, thus enabling the creation of an assistant tool in the future.

Exploring open source and proprietary LoRa mesh technologies

This paper explores low power wide area network (LPWAN) LoRa and its diverse variants, encompassing open-source and proprietary wireless mesh networks, operating over the physical LoRa or LoRaWAN layer. The primary challenge lies in defining an optimal LoRa mesh solution that balances cost-effectiveness, energy efficiency, low latency, long-range capability, and security. This study also comprehensively examines key LoRa mesh solutions from 2017 to 2024, as proposed by various authors. Furthermore, a detailed analysis is conducted to contrast open-source and commercial solutions, considering their applications, limitations, issues, characteristics, and pros and cons of mesh routing protocols. In the current landscape, the proliferation of open-source and proprietary LoRa mesh solutions has been instrumental in facilitating the connectivity of internet of things (IoT) devices. However, these solutions pose challenges related to energy consumption, latency, and suboptimal transmission throughput. These challenges are influenced by various LoRa characteristics such as spectrum factor, bandwidth, and transmission power, which directly impact the transmission range. Our research aims to perform a comparative analysis of existing LoRa mesh solutions by, systematically studying their advantages and disadvantages. This analysis offers valuable insights for making informed choices among these solutions in diverse domains for IoT applications.

Hydrogen-Powered Bicycle for Sustainable Mobility

Abstract: In the pursuit of sustainable transportation solutions, the integration of hydrogen fuel cells presents at the bicycles. This paper explores the high-level design considerations for a hydrogen-powered bicycle, focusing on key components such as the fuel cell system, hydrogen storage, powertrain, and overall vehicle architecture. The fuel cell system is a critical component, converting hydrogen gas into electricity to power an electric motor. The hydrogen storage system must be lightweight, compact, and safe, utilizing advanced materials and technologies to store hydrogen at high pressures. The powertrain of the hydrogenpowered bicycle involves the integration of the electric motor with the bicycle's drivetrain, ensuring efficient power delivered to the wheels. The overall vehicle architecture considers the integration of these components into a functional, user-friendly, and aesthetically pleasing design. Additionally, the paper discusses the environmental impact of hydrogen-powered bicycles, comparing them to traditional bicycles and other forms of transportation. The potential benefits of hydrogen-powered bicycles include zero-emission operation, long-range capabilities, and rapid refuelling times. Overall, the development of hydrogenpowered bicycles has the potential to revolutionize urban mobility, offering a clean, efficient, and sustainable alternative to traditional transportation methods.

Development of Two Wheel Drive Electric Bikes for Extreme Road and A Long-Range Capabilities

This paper aims to develop the electric bicycle by using a two-wheel drive that has a long range of use. This development is motivated by many extreme roads and the absence of a charging station except in the user’s own house. A folding bicycle type bicycle for adults with 16-inch wheels was used in this study. The two-wheel drive can be adjusted using the driving motor to be more flexible and adapt to road conditions, although the motor power used is small, 350-Watt 24 Volt for one wheel. The battery capacity used is quite large for the range quite far away, which is 24 volts 80 Amps, and the charging time is about 2 hours. The placement of the battery has calculated the center of gravity and balance of the bike. Results show that this electric bicycle can be used for slippery road conditions and slopes of not more than 1A maximum speed of the bicycle can reach up to 30 km/hour, on flat road conditions. Likewise, the bicycle’s range for a full charge is around 220-260 km, with an average speed of 15-16 km/hour. Two drives can be implemented independently, adjusting the running conditions by moving the drive motor selection button. For extreme conditions, it is recommended to use two electric motors.

TRANSMISSION, STORAGE AND PREPROCESSING OF DATA RECEIVED FROM SENSORS USING LORA TECHNOLOGY

This study focuses on the use of Internet of Things technologies to monitor air quality parameters in the city. The research included the development of a system for collecting data from sensors of temperature, humidity, pressure, gases, time, GPS for various environmental parameters. The article discusses the benefits of using LoRaWAN for data transmission, highlighting its low power consumption and long-range capabilities. The presented architecture allows for system scalability, emphasizing the ability to integrate with additional devices and sensors for more complete and comprehensive environmental monitoring. The collected data is stored in a MySQL database management system and the importance of proper data structuring and normalization is emphasized to ensure accurate analysis. In addition, a data preprocessing process is described to solve the problem of heterogeneity of data obtained from different sensors. The result of the study is the obtained and preprocessed data. The work also highlights the importance of data management to ensure the successful implementation of such systems in the face of heterogeneity of information from different sensors. Thus, the article presents a comprehensive approach to air quality monitoring using IoT and highlights the importance of proper data management for subsequent accurate analysis.

Improving the Reliability of Long-Range Communication against Interference for Non-Line-of-Sight Conditions in Industrial Internet of Things Applications

LoRa technology, renowned for its low-power, long-range capabilities in IoT applications, faces challenges in real-world scenarios, including fading channels, interference, and environmental obstacles. This paper aims to study the reliability of LoRa in Non-Line-of-Sight (NLoS) conditions and in noisy and mobile environments for Industrial IoT (IIoT) applications. Experimental measurements consider factors like vegetation and infrastructure, introducing mobility to replicate NLoS conditions. Utilizing an open-source LoRa Physical Layer (PHY) Software-Defined Radio (SDR) prototype developed with GNU Radio, we assess communication reliability through metrics such as Block Error Rate (BLER), Signal-to-Noise-Interference-plus-Noise Ratio (SINR), and data rate. The study reveals the estimated overall reliability of the LoRa signal at 90.23%, emphasizing specific configuration details. This work contributes to the broader field of LoRa communication, encompassing hardware, software, protocols, and management, enhancing our understanding of LoRa’s dependability in challenging IIoT environments.

Biosymbiotic platform for chronic long-range monitoring of biosignals in limited resource settings.

Remote patient monitoring is a critical component of digital medicine, and the COVID-19 pandemic has further highlighted its importance. Wearable sensors aimed at noninvasive extraction and transmission of high-fidelity physiological data provide an avenue toward at-home diagnostics and therapeutics; however, the infrastructure requirements for such devices limit their use to areas with well-established connectivity. This accentuates the socioeconomic and geopolitical gap in digital health technology and points toward a need to provide access in areas that have limited resources. Low-power wide area network (LPWAN) protocols, such as LoRa, may provide an avenue toward connectivity in these settings; however, there has been limited work on realizing wearable devices with this functionality because of power and electromagnetic constraints. In this work, we introduce wearables with electromagnetic, electronic, and mechanical features provided by a biosymbiotic platform to realize high-fidelity biosignals transmission of 15 miles without the need for satellite infrastructure. The platform implements wireless power transfer for interaction-free recharging, enabling long-term and uninterrupted use over weeks without the need for the user to interact with the devices. This work presents demonstration of a continuously wearable device with this long-range capability that has the potential to serve resource-constrained and remote areas, providing equitable access to digital health.

Assessment of long-range distributed acoustic sensing (DAS) capabilities in controlled environments

Distributed Acoustic Sensing (DAS) is an emerging technology enabling the recording of disturbances along fiber-optic (FO) cables with a wide range of applications, such as monitoring marine fauna, anthropogenic activities, and ocean climate. Despite the extensive research on DAS technology, its long-range capabilities have not been structurally studied yet. We present results of a sequence of purposefully designed experiments of DAS capabilities in (1) a laboratory, (2) a pool, and (3) a marine facility. To simulate long cables, we use combinations of FO coils 10–200 km in length. In the laboratory, realistic strain signals are simulated by an FO stretcher. In the pool, realistic acoustic signals are transmitted by an underwater speaker. At the marine facility, a combination of playback and real sound sources is used. Simultaneously deployed hydrophones allow DAS calibration and performance assessment. In this series of experiments, we measure internal noise, compare different DAS equipment, and successively optimize acquisition parameters for each interrogator performing at different, long sensing ranges in increasingly realistic environments. We show that long-range capabilities are strongly dependent on DAS settings (optical power, pulse repetition frequency, gauge length, pulse width) and vary between different interrogators.

LoRaWAN CubeSat with an Adaptive Data Rate: An Experimental Analysis of Path Loss Link Margin

One of the challenges of the Internet of Things (IoT) is to provide connectivity to devices around the globe. Long Range (LoRa) is one of the most practical technologies due to its low-power and long-range capabilities to be used by the Low Earth Orbit (LEO) CubeSat. This study aims to evaluate the performance of the Long Range Wide Area Network (LoRaWAN) in receiving uplink messages from ground sensor nodes at an altitude of 550 km with a maximum elevation angle of 0°. An Adaptive Data Rate (ADR) is applied for the dynamic signal reception with respect to receiving signal strength. In this study, the path loss is simulated using attenuation levels from 30–150 dB to ensure that the signal connectivity success rate is at a minimum elevation angle and to perform the link analysis under various conditions. The results show that the LoRaWAN signals are successfully received with an SNR of −21 at the 150 dB attenuation from the end nodes because of its spread-spectrum technique which allows the system to detect signals under the noise floor.

LORA Based Forest Fire Monitoring System

The LoRa-based forest fire monitoring method by using wireless type networks is an IoT system designed to detect and prevent forest fires. The system consists of sensor nodes which are deployed throughout the forest to monitor various environmental conditions such as humidity, temperature, wind speed and direction. These sensor nodes are equipped with LoRa radios that enable them to communicate wirelessly with a central gateway. The Gateway gathers the data from the sensor nodes and transmits it to a server in the cloud for processing and analysis. The system utilizes machine learning algorithms to analyse the collected data and detect any anomalies that may indicate the forest fire. In the event of a fire, the system can alert local authorities and fire departments, providing them with real-time information about the location and severity of the fire. This allows for faster response times and more efficient management of the fire. The LoRa-based forest fire prevention system using wireless networks offers several advantages over traditional forest fire detection systems. Its low-power, long-range capabilities enable it to cover large areas, making it ideal for monitoring vast forested areas. Additionally, its wireless connectivity eliminates the need for physical infrastructure such as cables, which can be expensive and time-consuming to install. Overall, the LoRa-based forest fire prevention system using wireless networks is a promising solution for preventing and managing forest fires. Its innovative use of IoT technology and machine learning algorithms can help to reduce the impact of forest fires and protect both human life and the environment.

LoRa-based IoT applications on campus: experimental demonstrations and performance evaluation

Lora technology is widely used in solving many IoT problems because of its long-range capability and low-cost. However, the model which works in the 2.4GHz frequency and without regional limitations is a novelty and its full capabilities are unknown. In this research the device is test for its transmission capabilities on a university campus because this is the conditions with high 2.4GHz interference from Wi-Fi, Bluetooth, etc. The authors also try to find the packet delivery rate and define at what distance LoRa end-node starts to lose connection with its gateway. Along the way receiving signal strength indicator is registered in order to understand the device power level. All of it is done by placing the gateway in the middle of the campus so that it equally reaches the furthermost points, connecting it with a LoRa-based end-node and testing this connection by placing the end-node device in different spots within the area and analysing the connection. LoRa 2.4GHz has shown lower effectiveness in terms of distance in comparison with its sub-GHz counterparts. Receiving signal strength indicator also demonstrated a lower power level in comparison with the mentioned device specifications. However, the LoRa technology still provides bigger distance than Wi-Fi or Bluetooth and is cheaper than other protocols used in IoT. Higher results can be achieved by using a better antenna and by eliminating physical obstacles.

LoRaWAN Security: An Evolvable Survey on Vulnerabilities, Attacks and their Systematic Mitigation

The changing vulnerability and threat landscape constantly challenge the security of wireless communication standards and protocols. For the Internet of Things (IoT), LoRaWAN is one of the dominant technologies for urban environments, industrial settings, or critical infrastructures due to its low-power and long-range capabilities. LoRaWAN IoT deployments are expected to operate for multiple years or even decades. Hence, it is imperative to maintain operational security at all times while continuously evolving the security of the standard and its implementations. We survey LoRaWAN security and follow a systematic and evolvable approach that can be dynamically updated. To this end, we propose a novel methodology to create evolvable surveys which relate the analyzed critical security concepts, thus allowing IT security experts to reason about LoRaWAN security properties over time. With this, we provide a tool to hardware manufacturers, software developers and providers, and network operators to achieve sustainable security for IoT deployments.

Histogram formation and noise reduction in biaxial MEMS-based SPAD light detection and ranging systems

In many applications, there is a great demand for reliable, small, and low-cost three-dimensional imaging systems. Promising systems for applications such as automotive applications as well as safe human robotic collaboration are light detection and ranging (lidar) systems based on the direct time-of-flight principle. Especially for covering a large field of view or long-range capabilities, the previously used polygon-scanners are replaced by microelectromechanical systems (MEMS)-scanners. A more recent development is to replace the typically used avalanche photodiodes with single-photon avalanche diodes (SPADs). The combination of both technologies into a MEMS-based SPAD lidar system promises a significant performance increase and cost reduction compared with other approaches. To distinguish between signal and background/noise photons, SPAD-based detectors have to form a histogram by accumulating multiple time-resolved measurements. In this article, a signal and data processing method is proposed, which considers the time-dependent scanning trajectory of the MEMS-scanner during the histogram formation. Based on known reconstruction processes used in stereo vision setups, an estimate for an accumulated time-resolved measurement is derived, which allows to classify it as signal or noise. In addition to the theoretical derivation of the signal and data processing, an implementation is experimentally verified in a proof-of-concept MEMS-based SPAD lidar system.

Fine-Scale Phase-Based Ranging Through Walls and Obstructions Using Tunneling RFID Tags

Tunneling tags have already shown their long-range capability for communications and localization in line-of-sight (LoS) with a reader operating in the 5.8 GHz band. In this paper, a received signal phase-based positioning method is investigated using semi-passive and tunneling radio frequency identification (RFID) tags in various non-line-of-sight (NLoS) environments. Experimental results show that a tunneling tag achieves gains above 10.2 dB and 19.6 dB when communicating through a cinder block and a plaster wall, respectively. When using the tunneling tag, with proper calibration, an average distance estimation accuracy of 1.33% and 2.37% is achieved in a hallway and classroom environment with clear LoS. An average estimation error of 1.03% and 2.12% is observed in through-obstruction and through-wall NLOS conditions, respectively.

Calibration of Planar Reflectors Reshaping LiDAR's Field of View.

This paper describes the calibration method for calculating parameters (position and orientation) of planar reflectors reshaping LiDAR’s (light detection and ranging) field of view. The calibration method is based on the reflection equation used in the ICP (Iterative Closest Point) optimization. A novel calibration process as the multi-view data registration scheme is proposed; therefore, the poses of the measurement instrument and parameters of planar reflectors are calculated simultaneously. The final metric measurement is more accurate compared with parameters retrieved from the mechanical design. Therefore, it is evident that the calibration process is required for affordable solutions where the mechanical design can differ from the inaccurate assembly. It is shown that the accuracy is less than 20 cm for almost all measurements preserving long-range capabilities. The experiment is performed based on Livox Mid-40 LiDAR augmented with six planar reflectors. The ground-truth data were collected using Z + F IMAGER 5010 3D Terrestrial Laser Scanner. The calibration method is independent of mechanical design and does not require any fiducial markers on the mirrors. This work fulfils the gap between rotating and Solid-State LiDARs since the field of view can be reshaped by planar reflectors, and the proposed method can preserve the metric accuracy. Thus, such discussion concludes the findings. We prepared an open-source project and provided all the necessary data for reproducing the experiments. That includes: Complete open-source code, the mechanical design of reflector assembly and the dataset which was used in this paper.

Optimization of the trimming tilting angle of the electric tiltrotor propeller group

The paper examined the possibility of improving the energy efficient performance of an electric tiltrotor with a lift-propulsion propeller group for a steady flight mode by reducing the energy consumption of the propeller group per unit of time or per unit of the path traveled by the electric tiltrotor. This is achieved by selecting the optimal tilting angles of the electric tiltrotor total thrust vector. In the proposed approach, the trimming tilting angle of the propeller group is variable, depending on the aerodynamic characteristics of the electric tiltrotor, its propeller group. Since the propeller group is equipped with the drives for tilting them, this approach is easily implemented by the conventional facilities of the electric tiltrotor. The tilting of the total thrust vector, on the one hand, leads to an increase in the effective value of the aerodynamic lift coefficient and, on the other hand, it is accompanied by a decrease in the projection of the total thrust vector on the flight speed vector, a change in the drag and power required to create the thrust of the propeller group. This circumstance makes it necessary to solve the optimization problem in order to increase the maximum endurance and long-range capabilities in the cruise mode of the electric tiltrotor flight. The paper presents a method for calculating the optimal tilting angles of the total thrust vector based on the equations of steady motion of the electric tiltrotor in the cruise flight mode, the expression for the total power required for the rotation of the propellers of the propeller group. The analytical dependences for the optimal tilting angles of the total thrust vector are obtained depending on the ratio of the wing area to the total propeller-disk area of the propeller group and the aerodynamic quality of the electric tiltrotor.

GLOBALIZATION – A FORM OF MANIFESTATION OF THE HYBRID WAR

Abstract: The growing scale and diversity of specific events of globalization, taking place on a global scale in the first two decades of the 21st century prove indisputably that actions assimilated to the hybrid warfare have become the most significant threat to nations. Unlike conventional warfare, hybrid forms do not involve direct or declarative actions of open conflict, but rather involve complex issues that are constantly unfolding and that are constantly evolving. Like globalization, the conflict no longer has a geographical delimitation or an infrastructure component, and populations are no longer the main fighters of these conflicts. In this article I will seek to answer some questions about the phenomenon of globalization and its implications for amplifying the manifestations of hybrid warfare in the contemporary operational environment, especially those of a cyber, terrorist, climatological, biological and organized crime nature, while presenting the concerns of international actors for increasing investments in research in the armament industry, improving military intelligence and long-range capabilities, in order to use military power as a tool of intimidation in foreign policy, active involvement of forces in punishing actors on the “axis of evil”, as well as the partial recovery of old areas of influence at regional or global level.

The US tri-service maritime strategy

The three US maritime services – the Navy, Marines Corps and Coast Guard – released a joint strategy in December 2020 describing their view of how to modernise their force structures and operational concepts, largely in response to the rise of China and the increasing use of long-range precision-strike capabilities. Among other things, the strategy calls for an emphasis on ‘day-to-day operations’ in situations short of crisis or war; for new types of expeditionary operations to deny adversaries access to the sea; and for investments in technologies such as advanced uninhabited platforms.

The NederDrone: A hybrid lift, hybrid energy hydrogen UAV

Many Unmanned Air Vehicle (UAV) applications require vertical take-off and landing and very long-range capabilities. Fixed-wing aircraft need long runways to land, and electric energy is still a bottleneck for helicopters, which are not range efficient. In this paper, we introduce the NederDrone, a hybrid lift, hybrid energy hydrogen-powered UAV that can perform vertical take-off and landings using its 12 propellers while flying efficiently in forward flight thanks to its fixed wings. The energy is supplied from a combination of hydrogen-driven Polymer Electrolyte Membrane fuel-cells for endurance and lithium batteries for high-power situations. The hydrogen is stored in a pressurized cylinder around which the UAV is optimized. This work analyses the selection of the concept, the implemented safety elements, the electronics and flight control and shows flight data including a 3h38 flight at sea while starting and landing from a small moving ship.

Experimental Link Quality Analysis for LoRa-Based Wireless Underground Sensor Networks

A variety of industrial applications are deployed in underground environments, such as soil condition assessment and pipeline monitoring (PM). Wireless underground sensor networks (WUSNs) are capable of continuously monitoring pipelines and promptly alerting any anomaly of entities. However, underground soils significantly influence the traditional WUSNs connectivity success. Long range (LoRa), being a leading low-power wide-area networks (LPWANs) technology, provides a new solution for underground industrial monitoring with its advantages in long-range capability and ultralow power consumption. Nevertheless, the LoRa-based link quality characteristics have not yet been quantitatively evaluated for WUSNs. In this article, the channel models of both the underground-to-aboveground (UG2AG) and aboveground-to-underground (AG2UG) communications are investigated. We experimentally analyze the impact of the propagation direction, burial depth and LoRa physical layer parameters on the in-situ LoRa propagation performance. The received signal strength indictor (RSSI), signal-to-noise ratio (SNR), and packet deliver ratio (PDR) are characterized for both communication channels in LoRa-based WUSNs. The semiempirical path-loss models are successfully verified by our field results, and we demonstrate that the communication range can be greater than 50 m at the burial depth of 0.4 m by adjusting the LoRa transmission/receiving settings. The combination of RSSI and SNR can be a better indicator of PDR than relying on either of them alone. Finally, the frame error rate (FER) is calculated to estimate the link performance with EM interferences. These results successfully demonstrate the advantages of LoRa for PM applications, which serve the first step toward the efficient protocol development of LoRa-based WUSNs.