Transmission Range Research Articles

Cationic Coordination Modification Drives Birefringence and Nonlinear Effect Double Lifting in Sulfate.

As nonlinear optical (NLO) crystals, sulfates have the superiority of transparency for ultraviolet (UV) light, but they are often troubled by small nonlinear coefficients and birefringence owing to the high symmetry of the [SO4]2- group. By introducing two neutral diethylenetriamine (DETA) molecules to replace the six coordinated water molecules of the [Zn(H2O)6]2+ complex cation in [Zn(H2O)6](SO4)(H2O), a new sulfate with an acentric structure, namely, [Zn(DETA)2](SO4)(H2O)3, has been designed and synthesized. Structural investigation reveals that the coordination modification of Zn2+ ion tremendously enhances its intraoctahedral distortion. The formed distorted [Zn(DETA)2]2+ cations and the [SO4]2- groups feature an optimized arrangement, endowing [Zn(DETA)2](SO4)(H2O)3 with enhancements in both second harmonic generation (SHG) intensity, from undetectable to 0.25 × KH2PO4 (KDP), and birefringence, from 0.014 to 0.042 at 1064 nm. Despite the slight compromise made in the light transmission range, [Zn(DETA)2](SO4)(H2O)3 still possesses a short absorption edge of 220 nm, retaining the majority of the light transmission range in the solar-blind region. Our work provides a novel and applicable approach of cationic coordination modification to improve the nonlinear optical coefficient and birefringence of sulfates.

LI-FI Performance Analysis in Various Aquatic Environments for Reliable Underwater Communication

The ability to communicate reliably and quickly underwater has been one of the driving forces behind the development of alternative technologies to conventional radio frequency systems. This study explores the performance of Light Fidelity (Li-Fi), a high-speed optical wireless communication technology, in diverse aquatic environments like fresh water, salt water, and turbid water. It evaluates key parameters like signal attenuation, data rate, bit error rate, and transmission range. Results show that Li-Fi offers significant advantages in bandwidth and data rate over traditional methods, but its efficiency is highly dependent on environmental conditions. The study recommends optimizing Li-Fi systems for reliable underwater communication, paving the way for enhanced underwater networking and data transmission applications.

Acoustic Sensors data transmission integrity and endurance with IoT-enabled location-aware framework

Environmental monitoring and disaster mitigation are critical applications of underwater acoustic sensor networks (UASNs). However, UASNs face significant challenges, including high latency, limited bandwidth, and energy constraints. This study introduces an Internet of Things (IoT)-driven location-aware framework (ILAF) designed to enhance UASN performance by utilizing non-GPS geographic coordinates for determining the location of sensor and sink nodes, identifying their neighbors based on coordinates and transmission range, and optimizing node placement and routing without the need for GPS modems. The framework is compared with several state-of-the-art protocols, including Bald Eagle Search inspired optimized energy efficient routing protocol (BES-OEERP) and IoT-enabled depth-based routing technique (IDBR), demonstrating superior performance. Specifically, ILAF achieved a packet delivery ratio (PDR) of 99%, which outperforms energy-efficient region-based source distributed routing algorithm (EERSDRA) (98%) and energy-efficient geo-opportunistic routing protocols (EEGORP) (96%). Additionally, ILAF reduced energy consumption by 20% compared to these existing protocols. These improvements result in a more energy-efficient network with fewer dead nodes (12 after 1,000 rounds) and higher throughput (5.7 kbps at 1,000 rounds), making ILAF suitable for real-time underwater applications. Future research will explore integrating lightweight IoT protocols like Message Queue Telemetry Transport (MQTT) and Constrained Application Protocol (CoAP) to enhance the framework’s performance and reliability further.

A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batteryless IoT Networks

The rapid advancement of Internet of Things (IoT) networks has revolutionized modern connectivity by integrating many low-power devices into various applications. As IoT networks expand, the demand for energy-efficient, batteryless devices becomes increasingly critical for sustainable future networks. These devices play a pivotal role in next-generation IoT applications by reducing the dependence on conventional batteries and enabling continuous operation through energy harvesting capabilities. However, several challenges hinder the widespread adoption of batteryless IoT devices, including the limited transmission range, constrained energy resources, and low spectral efficiency in IoT receivers. To address these limitations, reconfigurable intelligent surfaces (RISs) offer a promising solution by dynamically manipulating the wireless propagation environment to enhance signal strength and improve energy harvesting capabilities. In this paper, we propose a novel deep reinforcement learning (DRL) algorithm that optimizes the phase shifts of RISs to maximize the network’s achievable rate while satisfying IoT devices’ energy harvesting constraints. Our DRL framework leverages a novel six-dimensional chimp optimization algorithm (6DChOA) to fine-tune the hyper-parameters, ensuring efficient and adaptive learning. The proposed 6DChOA-DRL algorithm optimizes RIS phase shifts to enhance the received power of IoT devices while mitigating interference from direct and RIS-cascaded links. The simulation results demonstrate that our optimized RIS design significantly improves energy harvesting and achievable data rates under various system configurations. Compared to benchmark algorithms, our approach achieves higher gains in harvested power, an improvement in the data rate at a transmit power of 20 dBm, and a significantly lower root mean square error (RMSE) of 0.13 compared to 3.34 for standard RL and 6.91 for the DNN, indicating more precise optimization of RIS phase shifts.

Development of a Long-Range IoT Air Quality Monitoring System Using LoRa Mesh Repeaters for Real-Time Pollution Tracking

Numerous researchers are currently presenting innovative methods to measure air quality in a cost-effective and real-time manner. The primary significance of the air quality monitoring system lies in its ability to facilitate communication via the Internet. This capability enables monitoring stations to measure air quality over extensive regions, spanning several kilometers. Presently, existing technology has constraints on transmitting data beyond distances of a few kilometers. This study introduces an air quality monitoring station capable of measuring NO2, SO2, CO2, CO, PM2.5, and PM10. To extend the transmission range, a LoRa mesh repeater was designed, utilizing point-to-point LoRa technology for extended data transmission. The signal strength between the air quality monitoring station and the repeater varies from -84 dBm to -92 dBm. The observed RSSI signal between the LoRa repeater and the LoRa gateway in the experimental results varies from -69 dBm to -112 dBm. The practical, effective operating distance is 1.7 km, making it suitable for potential utilization in long-distance IoT applications.

Enhanced Triboelectric Outputs from PAN/MoS2 Nanofiber‐Based Nanogenerators for Powering Backscatter Communications in Sustainable 6G Networks

This work explores the development of a triboelectric nanogenerator (TENG) based on polyacrylonitrile (PAN) and molybdenum disulfide (MoS2) nanosheets composite fibers for enhancing tribo‐positive electricity to power backscatter communication systems, contributing to the sustainable internet of things (IoT) nodes in future 6 G networks. By incorporating different concentrations of MoS2 (1, 2, 3, and 4 wt%) nanosheets into PAN nanofibers via electrospinning, the nanocomposite fiber‐based TENGs exhibit improved triboelectric properties. The TENG based on PAN/4% MoS2 nanocomposite fiber mat achieve a peak open‐circuit voltage of 296 V and a short‐circuit current of 6.16 μA, which represents an ≈95% and 77% enhancement, respectively, in comparison with the TENGs based on neat PAN nanofiber mat. The enhanced charge transfer ability at the PAN and MoS2 nanosheet interface, the increased dielectric properties, the rougher surface morphology of the composite nanofibers contribute to the enhancements in triboelectric performance. These TENGs are integrated with the backscatter communication system to power a wireless identification and sensing platform (WISP) tag, demonstrating extended transmission range and improved real‐time data acquisition. These findings suggest that TENGs can play a significant role in sustainable energy solutions for 6 G‐enabled IoT applications.

Conformal multi-channel MIMO antenna for implantable leadless transcatheter pacing systems

This article presents a conformal multi-channel multiple-input-multiple-output (MIMO) antenna designed for a leadless transcatheter pacing system (TPS), operating across the medical implants communications services (MICS) band (401–406 MHz), the wireless medical telemetry services (WMTS) bands (0.608 GHz and 1.4 GHz), and the industrial, scientific and medical (ISM) bands (0.433 GHz, 0.915 GHz, and 2.45 GHz). The proposed antenna has a size of 19 mm × 10 mm × 0.068 mm (0.047λg × 0.025λg × 0.0001λg), and it is constructed on a thin polyimide substrate and wrapped around the TPS capsule’s inner wall, efficiently utilizing the inner space. For the simulation, the proposed antenna and TPS capsule containing dummy electronics are positioned within a homogeneous three-layered phantom (skin-fat-heart) with dielectric properties that mimic the human heart, as well as in a realistic heterogeneous voxel model (Gustav). The antenna is validated for a real environment using an ex-vivo setup comprised of fabricating the antenna prototype and measuring its performance metrics inside pork meat and phantom solution. The proposed MIMO antenna offers good isolation (>25 dB) between antenna elements, and the impedance bandwidths are 710 MHz (0.34 to 1.05 GHz), 560 MHz (1.26 to 1.82 GHz), and 990 MHz (2.01 to 3 GHz). Further, MIMO characteristics are evaluated, and antenna robustness and safety are tested by considering specific absorption rates using human voxel models. The proposed MIMO antenna is the thinnest conformal antenna designed to cover essential biotelemetry frequency bands, including low frequencies of 0.402 GHz and 0.433 GHz with circular polarization, which significantly reduces power consumption and improves transmission range, making it a viable candidate for wireless TPS applications.

Thermal properties of fluoride fiber Bragg gratings at high to cryogenic temperatures.

The thermal sensitivity of fiber Bragg gratings (FBGs) is extensively employed in diverse industrial and scientific applications. FBGs lie at the core of flexible, low-cost, and highly precise sensors, featuring stability in harsh environments and distributed sensing capability. This study assesses the thermal properties of FBGs in fluoride fibers within a temperature range of 4-373 K. Despite having higher thermal expansion coefficients, FBGs in the near-IR wavelength range do not exhibit high sensitivity at room or higher temperatures. However, the pronounced enhancement of their thermal sensitivity at longer Bragg wavelengths shows the potential for sensing applications in the light of the fluoride glass extended transmission range up to 4-5.5 µm. Most importantly, employing FBGs inscribed in fluoride fibers enables the further expansion of fiber-based sensors to cryogenic environments, as they exhibit a detectable sensitivity of 0.5-1.7 pm/K below 50 K. Overall, the exposure to low temperatures provides valuable information on glass stability and physical parameters, which is beneficial for the further development of photonic systems based on fluoride fibers.

IoT-Enhanced Decision Support System for Real-Time Greenhouse Microclimate Monitoring and Control

Greenhouses have taken on a fundamental role in agriculture. The Internet of Things (IoT) is a key concept used in greenhouse-based precision agriculture (PA) to enhance vegetable quality and quantity while improving resource efficiency. Integrating wireless sensor networks (WSNs) into greenhouses to monitor environmental parameters represents a critical first step in developing a complete IoT solution. For further optimization of the results, including actuator nodes to control the microclimate is necessary. The greenhouse must also be remotely monitored and controlled via an internet-based platform. This paper proposes an IoT-based architecture as a decision support system for farmers. A web platform has been developed to acquire data from custom-developed wireless sensor nodes and send commands to custom-developed wireless actuator nodes in a greenhouse environment. The wireless sensor and actuator nodes (WSANs) utilize LoRaWAN, one of the most prominent Low-Power Wide-Area Network (LPWAN) technologies, known for its long data transmission range. A real-time end-to-end deployment of a remotely managed WSAN was conducted. The power consumption of the wireless sensor nodes and the recharge efficiency of installed solar panels were analyzed under worst-case scenarios with continuously active nodes and minimal intervals between data transmissions. Datasets were acquired from multiple sensor nodes over a month, demonstrating the system’s functionality and feasibility.

MIMO and PDM-based intersatellite optical link for high-speed data transfer and remote sensing application.

Inter-Satellite Optical Wireless Communication (Is-OWC) is a pivotal technology for advancing global connectivity and the effectiveness of space-based operations. It serves as the linchpin for various applications such as global internet coverage, Earth observation, and remote sensing, bolstering our capacity to monitor the planet and deliver essential services. This paper presents the design and performance evaluation of a Polarization Division Multiplexing (PDM) and Multiple Input Multiple Output (MIMO)-based Is-OWC system operating at a data rate of 60 Gbps. The system was tested under varying transmission distances, atmospheric turbulence, and pointing error conditions. At a transmission distance of 10,000 km, the system achieved a Bit Error Rate (BER) of 6.76 × 10⁻3 for Channel 1 (X polarization) and 7.1 × 10⁻3 for Channel 4 (Y polarization), both within Forward Error Correction (FEC) limits. The introduction of a 4 × 4 MIMO configuration extended the transmission range to 14,000 km, with a corresponding BER of 9.1 × 10⁻3 for Channel 1 and 8.7 × 10⁻⁵ for Channel 4. Eye diagrams confirm successful signal reception, demonstrating that the system can maintain high data rates and low error rates over long distances. The proposed PDM-MIMO system showcases high-capacity, robust performance under challenging conditions, such as turbulence and pointing errors, validating its suitability for space-based communication applications. These findings highlight the potential of the system for future deployments in satellite networks, offering reliable, high-throughput, and low-latency data transmission over extended distances.

Fully Wireless, In Vivo Assessment of Superimposed Physiological Vital Signs Using a Biodegradable Passive Tag Interrogated with a Wearable Reader Patch

AbstractState‐of‐the‐art biosignal monitoring systems strive to achieve a balance between biocompatibility, biodegradability, and miniaturized, unobtrusive signal acquisition, thus requiring further research for improved user safety, mobility, and comfort. Here, a fully wireless sensing system is presented for real‐time in vivo assessment of physiological vital signs, addressing these challenges to enhance performance and user experience. The system features a biodegradable passive tag with a nanoscale crack‐based strain gauge sensor connected to a coil antenna on a gelatin‐ionic liquid substrate (GIS). The thermal crosslinking in the GIS promotes adhesion, while the presence of ionic liquid decreases the self‐resonance frequency of the BCA to below 100 MHz, enabling the device to operate in detuned mode. A lightweight (1.547 g) wearable reader patch interrogates an implanted passive tag via near‐field inductive coupling and transmits sensory data to peripheral devices via Bluetooth. Thus, the system ensures minimal tissue absorption and extended transmission range while consuming ≈80 mW of power during operation. In vitro and in vivo studies, culminating in successful implementation within a rat model, validated the implanted tag's biocompatibility and the system's capability to wirelessly acquire and process superimposed physiological vital signs, highlighting its potential to enhance patient outcomes through improved diagnostic and monitoring practices.

Transmission and Host Range of Papaya Ring Spot Virus

Transmission and Host Range of Papaya Ring Spot Virus

Crystal Growth, Characterization, and Properties of Nonlinear Optical Crystals of Li0.5Ag0.5GaTe2 for Mid-Infrared Applications.

LiGaTe2 is a promising nonlinear optical crystal with a large figure of merit (d362/n3), but it is difficult to grow the LiGaTe2 single crystal due to its extreme instability. In this work, we used Ag to replace Li and successfully grew a Li0.5Ag0.5GaTe2 crystal by the modified Bridgman method for the first time. We found it has thermal stability below 200 °C in an atmospheric environment, and the thermal expansion coefficient is positive. This is different from LiGaTe2 and AgGaTe2 which have a negative thermal expansion coefficient along the c-axis. When the temperature exceeds 200 °C, Li0.5Ag0.5GaTe2 is easily decomposed and oxidized. Under closed vacuum conditions, the melting and solidifying points of Li0.5Ag0.5GaTe2 are measured to be 719 and 694 °C. XPS spectra show that the binding energies of Li, Ga, and Te are higher than LiGaTe2, and the surface is easily oxidized. The A1 vibration modes are found at 117.72 and 135.44 cm-1 by the Raman spectrum which is related to the Te and Ga-Te bond in [GaTe4]5- tetrahedra. Li0.5Ag0.5GaTe2 has a wide transmittance range from 0.94 to 20 μm, and there was two-photon absorption near 16 μm. The phonon spectrum and PDOS were simulated by the DFT calculation to study the phonon vibration modes in the lattice, which shows that the density of the Raman vibration is higher than those of AgGaTe2 and LiGaTe2. The SHG test results showed that the SHG response intensity of Li0.5Ag0.5GaTe2 is 1.5 times that of AgGaS2, which shows its excellent nonlinear optical properties for mid-IR applications.

Wireless Data Transmission through Concrete Structures

Chloride ion presence in the concrete pore solution is an important factor in the initiation of rebar corrosion. Therefore, elevated chloride concentration in the pore solution needs to be detected as early as possible. For this early detection to be achieved, it is ideal to deploy sensors inside the concrete structure itself. This allows real time sampling of the pore solution which is closest to the rebar. To achieve this one needs to have a system based on wireless communication which allow the sensors to communicate within the structure. This would avoid wired communications methods, which impart fragility and implementation difficulties. This literature review paper endeavours to look at the various types of radiation which can be harnessed to penetrate through the opaque concrete structure. Potential data transmission methods utilising Radio Frequency Radiation, Ultrasonic Radiation, X-Ray Radiation and Neutron Beam Radiation physics were reviewed and evaluated against a set of parameters. The paper scores each radiation type against System Size, Power Supply Requirements, Transmission Range, Complexity of Circuits and Safety issues. Through these scores, each transmission technology was graded on its potential to act as the basis on which to build a micrometre sized intra-concrete data transmission system. The paper shows that ultrasonic radiation is the most promising radiation technology for use in this application.

Wireless Data Transmission through Concrete Structures

Chloride ion presence in the concrete pore solution is an important factor in the initiation of rebar corrosion. Therefore, elevated chloride concentration in the pore solution needs to be detected as early as possible. For this early detection to be achieved, it is ideal to deploy sensors inside the concrete structure itself. This allows real time sampling of the pore solution which is closest to the rebar. To achieve this one needs to have a system based on wireless communication which allow the sensors to communicate within the structure. This would avoid wired communications methods, which impart fragility and implementation difficulties. This literature review paper endeavours to look at the various types of radiation which can be harnessed to penetrate through the opaque concrete structure. Potential data transmission methods utilising Radio Frequency Radiation, Ultrasonic Radiation, X-Ray Radiation and Neutron Beam Radiation physics were reviewed and evaluated against a set of parameters. The paper scores each radiation type against System Size, Power Supply Requirements, Transmission Range, Complexity of Circuits and Safety issues. Through these scores, each transmission technology was graded on its potential to act as the basis on which to build a micrometre sized intra-concrete data transmission system. The paper shows that ultrasonic radiation is the most promising radiation technology for use in this application.

Auto Aligning, Error-Compensated Broadband Collimated Transmission Spectroscopy.

Broadband spectral measurements of the ballistic transmission of scattering samples are challenging. The presented work shows an approach that includes a broadband system and an automated adjustment unit for compensation of angular distortions caused by non-plane-parallel samples. The limits of the system in terms of optimal transmission and detected forward scattering influenced by the scattering phase function are investigated. We built and validated a setup that measures the collimated transmission signal in a spectral range from 300 nm to 2150 nm. The system was validated using polystyrene spheres and Mie calculations. The limits of the system in terms of optimal transmission and detected forward scattering were researched. The optimal working parameters of the system, analyzed by simulations using the Monte Carlo method, show that the transmission should be larger than 10% and less than 90% to allow for a reliable measurement with acceptable errors caused by noise and systematic errors of the system. The optimal transmission range is between 25% and 50%. We show that the phase function is important when considering the accuracy of the measurement. For strongly forward-scattering samples, errors of up to 80% can be observed, even for a very small numerical aperture of 6.6·10-4, as used in our experimental system. We also show that errors increase with optical thickness as the ballistic transmission decreases and the multiscattered fraction increases. In addition, errors caused by multiple reflections in the sample layer were analyzed and also classified as relevant for classical absorption spectroscopy.

Reaction-sintered highly transparent MgGa2O4 ceramics with enhanced dielectric properties

Reaction sintering of MgO and Ga2O3 powders was first used to prepare MgGa2O4 transparent ceramics. The microstructural evolution suggested that the negligible volume change resulting from the solid-phase reaction of MgO and Ga2O3, as well as the close and homogeneous arrangement of both fine particles, are the key factors in obtaining pre-sintered ceramics with an ideal microstructure at lower temperature. After a hot isostatic pressing (HIP) treatment, the fully dense ceramic exhibited improved in-transmittance (74.7 %@600 nm, and 85.4 %@4401 nm) and quality factor (Q × f = 168,000 GHz). Due to the combination of high transparency, wide transmission range (6.22 μm at the 60 % transmittance), ultra-low dielectric loss, and near-zero temperature coefficient of resonance frequency (− 3.9 ppm/°C), transparent MgGa2O4 ceramic is suggested to be an ideal optical-dielectric integration material.

Enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery in wireless ad hoc networks

The utilization of directional antennas for neighbor discovery in wireless ad hoc networks brings notable benefits, such as extended transmission range, reduced transmission interference, and enhanced antenna gain. However, when nodes use directional antennas for neighbor discovery, the communication range is limited, resulting in a lack of knowledge of potential neighbors. Hence, it is necessary to design a special antenna direction switching strategy for neighbor discovery based on directional antennas. Traditional methods of switching antenna directions are often random or follow predefined sequences, overlooking the historical knowledge of sector exploration for antenna directions. In contrast, existing machine learning approaches aim to leverage observed historical knowledge to adjust antenna directions for faster neighbor discovery. Nonetheless, the latency of neighbor discovery is still high because the node cannot fully utilize the observed historical knowledge (i.e.., only using the knowledge observed by the node in transmission mode, ignoring the knowledge observed by the node in reception mode). Meanwhile, the corresponding reward and penalty mechanisms are still not detailed enough (i.e.., these reward and penalty mechanisms only consider the sectors of discovered and undiscovered neighboring nodes, ignoring the scenario of sectors that have been rewarded). In this paper, the neighbor discovery process is modeled as a reinforcement learning-based learning automaton. We propose an enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery algorithm, called ERTTND. The algorithm consists of a two-way transmit-receive reinforcement learning mechanism (TTRL) and an enhanced reward-and-penalty mechanism (ERAP). This algorithm leverages insights from nodes in transmission and reception modes to refine their tactical decisions. Then, through an enriched reward-and-penalty framework, nodes optimize their strategies, thus expediting neighbor discovery based on directional antennas in wireless ad hoc networks. Simulation results demonstrate that compared to existing representative algorithms, the proposed ERTTND algorithm can achieve over 30% savings in terms of average discovery delay and energy consumption.

Design and performance analysis of integrated sensing and communication scheme based on LoRa signals

LoRa (Long Range) has garnered widespread adoption in Internet of Things (IoT) communications due to its extensive transmission range and robust resistance to interference. Furthermore, its capability to linearly discern deviations across both frequency and time domains renders it an ideal signal for sensing applications. Consequently, this article proposes an Integrated Sensing and Communication (ISAC) scheme based on the LoRa signal. On the communication side, while the modulation and demodulation processes of the LoRa signal are currently kept confidential, this article has theoretically derived its principles and further implemented the communication functionality of LoRa through experimental simulations. On the sensing side, through theoretical derivation and experimental simulation, the influence of different modulation information on the peak amplitude and position of pulse compression was analyzed. Two signal processing schemes are proposed to overcome the impact of modulation information, thereby enabling the sensing function. The communication and sensing performance of the proposed ISAC scheme was evaluated. Experimental results demonstrated that, even in low signal-to-noise ratio (SNR) environments, the communication function maintained a low bit error rate (BER), while the sensing function achieved a high target detection rate, both of which exhibited excellent performance.

Security-enabled optimal placement of drone-assisted intelligent transportation systems in mission-critical zones

A massive increase in highly dynamic vehicular nodes has resulted in network instability. Owing to the heterogeneous vehicular environment requires a multi-objective solution using a meta-heuristic optimization algorithm in the event of mission-critical zones with poor signal and secured quick decision-making system. Developed a security-enabled optimal placement of Drones or unmanned aerial vehicles (UAV) in mission-critical zones aims to achieve two primary objectives: 1) Maximizing the effectiveness of the intelligent transportation system (ITS) for traffic management and ubiquitous connectivity in mission-critical zones. 2) Ensuring robust security measures to protect sensitive data and infrastructure. This approach represents a cutting-edge solution for optimizing transportation systems in high-risk environments while safeguarding against potential security threats. The pre-deployment of drones and vehicles (VOBU) parameter occurs during the registration phase, and then the mission-critical zone (MCZ) is identified and stored. The optimal position for drones in MCZs is determined by mathematically modeling a golden eagle optimization (GEO), which is inspired by varying the speed at different stages along their spiral trajectory for cruising and hunting. Furthermore, the robustness of the sensitive data and the real identity is ensured by using a biometric-based AKA algorithm utilizing the prevalent real-or-random (ROR) model and the formal security analysis. Based on a comparison of the simulation results, the proposed SDV-GEOAKA scheme outperforms the existing system- STPTC-A2 G, IoDAV, and IMOC with 99.36 % of PDR approximately, whereas, SDV-GEOAKA has maintained a load balancing factor with 0.01 to 0.1 when the transmission range between 0 and 60. When it comes to network coverage, proposed work outperforms with 99.95 % during the transmission range of 50 mW means it uses a minimum number of drones with maximum connectivity within the coverage range and also has significantly reduced the computation overhead and an increase in anomaly detection rate.