Military Applications Research Articles

Plant Density and Health Evaluation in Green Stormwater Infrastructure Using Unmanned-Aerial-Vehicle-Based Imagery

Over the past few decades, there has been a notable surge in interest in green stormwater infrastructure (GSI). This trend is a result of the need to effectively address issues related to runoff, pollution, and the adverse effects of urbanization and impervious surfaces on waterways. Concurrently, umanned aerial vehicles (UAVs) have gained prominence across applications, including photogrammetry, military applications, precision farming, agricultural land, forestry, environmental surveillance, remote-sensing, and infrastructure maintenance. Despite the widespread use of GSI and UAV technologies, there remains a glaring gap in research focused on the evaluation and maintenance of the GSIs using UAV-based imagery. This study aimed to develop an integrated framework to evaluate plant density and health within GSIs using UAV-based imagery. This integrated framework incorporated the UAV (commonly known as a drone), WebOpenDroneMap (WebDOM), ArcMap, PyCharm, and the Canopeo application. The UAV-based images of GSI components, encompassing trees, grass, soil, and unhealthy trees, as well as entire GSIs (e.g., bioretention and green roofs) within the Morgan State University (MSU) campus were collected, processed, and analyzed using this integrated framework. Results indicated that the framework yielded highly accurate predictions of plant density with a high R2 value of 95.8% and lower estimation errors of between 3.9% and 9.7%. Plant density was observed to vary between 63.63% and 75.30% in the GSIs at the MSU campus, potentially attributable to the different types of GSI, varying facility ages, and inadequate maintenance. Normalized difference vegetation index (NDVI) maps and scales of two GSIs were also generated to evaluate plant health. The NDVI and plant density results can be used to suggest where new plants can be added and to provide proper maintenance to achieve proper functions within the GSIs. This study provides a framework for evaluating plant performance within the GSIs using the collected UAV-based imagery.

Progress in Advanced Infrared Optoelectronic Sensors.

Infrared optoelectronic sensors have attracted considerable research interest over the past few decades due to their wide-ranging applications in military, healthcare, environmental monitoring, industrial inspection, and human-computer interaction systems. A comprehensive understanding of infrared optoelectronic sensors is of great importance for achieving their future optimization. This paper comprehensively reviews the recent advancements in infrared optoelectronic sensors. Firstly, their working mechanisms are elucidated. Then, the key metrics for evaluating an infrared optoelectronic sensor are introduced. Subsequently, an overview of promising materials and nanostructures for high-performance infrared optoelectronic sensors, along with the performances of state-of-the-art devices, is presented. Finally, the challenges facing infrared optoelectronic sensors are posed, and some perspectives for the optimization of infrared optoelectronic sensors are discussed, thereby paving the way for the development of future infrared optoelectronic sensors.

View for a future of UAVs in military applications

One of the most stable trends in recent years is the increase in the number of robotic equipment and complexes, primarily complexes with unmanned aerial vehicles (UAVs). The purpose of the work is to conduct a study of the prospects for military use of UAVs. The directions of the use of UAVs in military affairs are presented, as well as a list of scientific studies that need to be carried out for more effective use of UAVs. The presented material can be used to form programs for the development of military UAVs.

TARGET RECOGINITION AND DETECTION USING DEEP LEARING TECHNIQUE

Object detection is a fundamental computer vision function for identifying and locating things in images or videos. Unlike image classification, object detection not only classifies the items in an image but also locates them inside the picture by constructing a bounding box around each one. Defence objects include a wide range of key assets needed for military and security activities. Tanks, armoured personnel carriers (APCs), military trucks, planes, helicopters, naval boats, and unmanned ground vehicles (UGVs) are among the types of vehicles included. Detection of these vehicles is critical for tracking troop movements, analysing battlefield dynamics, and maintaining operational preparedness. The modern defence scenario demands improved surveillance and security measures to successfully counter growing threats. This work suggests using the You Only Look Once (YOLO) method for real-time identification of numerous defence items. The project's goal is to improve security by properly detecting a variety of items, including cars, individuals, equipment, and structures, with a single deep learning model. Methodologically, a broad dataset containing photos and videos of defence items in various locations is collected and preprocessed. The YOLO algorithm is then trained on this dataset, with parameters optimised for high accuracy and recall rates. Performance evaluation include thorough testing on various datasets to determine accuracy, speed, and resilience. KEYWORDS: Target recognition, Detection, YOLO algorithm, Military applications, Flying objects, Vehicles, Sensor integration, Real-time processing, Threat detection, Situational awareness.

Medicalizing Topography: The French Army and Mediterranean Climates, 1760-1860.

This article details how the French army employed medical topography as a tool of military occupation throughout the Mediterranean world from the mid-eighteenth to mid-nineteenth century. It departs from other works by focusing exclusively on medical topography's military applications. Medical topographies charted the connections between health and the environment by observing a location's features, such as soil, air, and water quality, as well as elevation, prevailing winds, common local diseases, sources of potential contagion, and the cleanliness of urban environments. Because a medical-topographic study took time to write and implement, its findings provided little utility during active conflict. Only after the fighting ceased during a campaign could the army make use of a medical topography's findings by taking measures such as draining swamps, relocating hospitals in unhealthy environments, and issuing climate-appropriate gear.

Terminal Trajectory Planning for Synthetic Aperture Radar Imaging Guidance Based on Chronological Iterative Search Framework.

Synthetic aperture radar (SAR) is capable of obtaining the high-resolution 2-D image of the interested target scene, which enables advanced remote sensing and military applications, such as missile terminal guidance. In this article, the terminal trajectory planning for SAR imaging guidance is first investigated. It is found that the guidance performance of an attack platform is determined by the adopted terminal trajectory. Therefore, the aim of the terminal trajectory planning is to generate a set of feasible flight paths to guide the attack platform toward the target and meanwhile obtain the optimized SAR imaging performance for enhanced guidance precision. The trajectory planning is then modeled as a constrained multiobjective optimization problem given a high-dimensional search space, where the trajectory control and SAR imaging performance are comprehensively considered. By utilizing the temporal-order-dependent property of the trajectory planning problem, a chronological iterative search framework (CISF) is proposed. The problem is decomposed into a series of subproblems, where the search space, objective functions, and constraints are reformulated in chronological order. The difficulty of solving the trajectory planning problem is thus significantly alleviated. Then, the search strategy of CISF is devised to solve the subproblems successively. The optimization results of the preceding subproblem can be utilized as the initial input of the subsequent subproblems to enhance the convergence and search performance. Finally, a trajectory planning method is put forward based on CISF. Experimental studies demonstrate the effectiveness and superiority of the proposed CISF compared with the state-of-the-art multiobjective evolutionary methods. The proposed trajectory planning method can generate a set of feasible terminal trajectories with optimized mission performance.

Design and analysis of SRR based metamaterial loaded circular patch multiband antenna for satellite applications

Satellite communication has reached a turning point in transmitting data quickly and receiving signals clearly in faraway places. This paper presents a metamaterial-based antenna for distant and military applications that overcomes restrictions and performs unmatched. This project explores metamaterials to create a unique antenna. Expect to be astounded by its power to bend electromagnetic waves, miniaturize, and change our relationship with the universe. The feeding mechanism of this antenna is a modified co-planar waveguide. At 5.6 GHz, the proposed antenna unit cell measures 0.076λ0×0.2λ0, making it small thanks to its MTM characteristic. CP radiation is made when two orthogonally polarized modes are stimulated at the same time and two composite right- and left-handed transmission line unit cells are placed orthogonally. Reduced size, increased bandwidth, and improved Learn how this discovery opens new doors for high-resolution photography, broadband internet, and space exploration. One nanostructure that makes up a metamaterial is the Split Ring Resonator (SRR). SRR dimensions must be smaller than the resonance wavelength, making them crucial for near-infrared and optical responses. This effort examined nanoscale SRR characteristics in the infrared and visible ranges. SRRs composed of aluminum (Al) and gold (Au) were produced on silicon and silica substrates using electron beam lithography (EBL). The proposed structure consists of a microstrip-line-supplied SRR, a parasitic patch that is perpendicular to the ground plane, and two via holes connected by two split rings that feed the patch indirectly. Choosing the right material parameter for all such antennas depends on the planned structure. Fabrication and testing of the antenna matched simulations. Dimensions: 23.7 mm × 16.2 mm × 1.6 mm; substrate dielectric constant: 4.4. Experimental data are detailed and compared to analytical calculations. Simulation results show that metamaterials have negative permittivity and permeability in a certain frequency range, which can be predicted by an analytical method. Simulations indicated eight BRS, WiMAX, radar, and mobile phone resonance frequencies. Radiation is dipole-like in the omnidirectional in the H-plane and E-plane. 10 dB return loss and 3 dB axial ratio bandwidths are 38.6.7% and 8.1%, respectively.

WITHDRAWN: Visualized neural network-based vibration control for pigeon-like flexible flapping wings

This study investigates pigeon-like flexible flapping wings, which are known for their low energy consumption, high flexibility, and lightweight design. However, such flexible flapping wing systems are prone to deformation and vibration during flight, leading to performance degradation. It is thus necessary to design a control method to effectively manage the vibration of flexible wings. This paper proposes an improved rigid finite element method (IRFE) to develop a dynamic visualization model of flexible flapping wings. Subsequently, an adaptive vibration controller was designed based on non-singular terminal sliding mode (NTSM) control and fuzzy neural network (FNN) in order to effectively solve the problems of system uncertainty and actuator failure. With the proposed control, stability of the closed loop system is achieved in the context of Lyapunov’s stability theory. At last, a joint simulation using MapleSim and MATLAB/Simulink was conducted to verify the effectiveness and robustness of the proposed controller in terms of trajectory tracking and vibration suppression.The obtained results have demonstrated great practical value of the proposed method in both military (low-altitude reconnaissance, urban operations, and accurate delivery, etc.) and civil (field research, monitoring, and relief for disasters, etc.) applications.

Exploring High-Voltage Sulfate Cathodes for Low-Temperature Thermal Batteries

Thermal batteries have high specific energy and can operate in harsh environments, making them suitable for military and aerospace applications. However, existing cathode materials do not meet the high power and energy density requirements of advanced military systems. This urgent need motivates the development of new high-performance cathodes. Sulfates, as polyanionic compounds with highly electronegative anions, often exhibit higher voltages than phosphates. This high voltage should match the high power output needs of thermal battery cathode, though few studies explore sulfate. In this of case, NiSO4, CoSO4, and CuSO4 were investigated as cathode materials for thermal battery. They all have higher voltage and greater specific capacity at 450 °C (cut-off voltage is 75% of peak voltage) than at 500 °C or higher. Compared with other temperatures, the peak voltage of CoSO4 cathode at 450 °C is 2.23 V and the specific capacity is 296 mAh g−1. While CuSO4 showed modest capacity at 450 °C, its high voltage of 2.5 V makes it a promising high energy density cathode. This work provides new insights into cathode materials for high power and energy density thermal batteries.

Study on nanosecond laser-induced iron plasma reactive etching of single-crystal CVD diamond

Single-crystal diamond has great potential applications in national defense, military, and aerospace fields. However, the high hardness, chemical inertness, and anisotropy bring great challenges to machine microstructures on the diamond. Here, iron plasma, generated by infrared nanosecond laser ablation of a Fe target, was utilized to etch single-crystal diamond. The EDS, Raman, and XPS analysis revealed the formation of iron carbide within the sputtered layer surrounding the diamond microgrooves, thereby confirming that the iron plasma reacts chemically with the diamond. It was observed that employing a reactive metal, such as iron, for etching diamond microgrooves yields improved morphological characteristics and enhanced etching efficiency compared to the use of a non-reactive metal, such as copper. Moreover, the process of material removal through laser-induced iron plasma etching of diamond was elucidated. Subsequently, a systematic investigation was conducted on the impact of processing parameters on the laser-induced iron plasma etching of diamonds. Various periodic microstructures with regular edges and no chipping and cracks were successfully processed on the diamond using suitable laser parameters. This study furnishes a novel approach for the efficient fabrication of high-quality microstructures on single-crystal diamonds.

A Review of Metamaterials Cloaking for Military and Civilian Use

Metamaterials cloaking technology boasts a wide array of potential uses, spanning from military stealth applications to advancements in medical imaging. Metamaterials are specially engineered materials with unique characteristics absent in natural substances, such as negative refractive index, empowering them to manipulate electromagnetic waves in novel ways. The process of cloaking with metamaterials involves the bending of light or other electromagnetic waves around an object, effectively rendering it invisible or significantly reducing its detectability. This is accomplished through the intricate design of metamaterial structures capable of governing the flow of electromagnetic fields, diverting them away from the cloaked object. Among the most prominent applications of metamaterial cloaking is the development of invisibility cloaks. While primarily at the experimental stage, researchers have made substantial progress in crafting cloaking devices capable of concealing objects from specific wavelengths of light. These cloaks function by manipulating the path of light around an object, effectively creating the illusion of its absence. The potential applications of metamaterial cloaking encompass a broad spectrum, including invisibility, antennas and sensors, medical imaging, wireless communication, and stealth technology.

Multifunctional Robot for Military Applications

Abstract: The fastest-growing and most fascinating field in the modern world is robotics. A robot's input and output can sense its surroundings and respond accordingly. Scientists have developed military robots through technological advancement and study. Indicate in this section what needs to be modified. After that, select the paraphrasing option below. This increases the security of a soldier's life in combat. Military robots are employed to carry out a number of dangerous jobs, including shooting opponents, detecting landmines, disarming live unexploded explosives, and monitoring combat zones. These combat robots are outfitted with integrated systems, including grippers, cameras, sensors, and actuators. Self-contained robots are required because of the issues that soldiers and civilians are facing with terrorism and insurgencies. Nations invest a great deal of money in the development of new defensive systems that can protect their citizens from terrorist threats. Through the use of a robotic system that can monitor a variety of field conditions and transmit data to an Android application over Wi-Fi, the suggested solution eventually offers a remote monitoring and controlling capability.

Software Simulator for MIL-STD-1553B Protocol Controller Chipset

Abstract: In recent times, due to the usage of avionics subsystems and the amount of data processed by them, there is an increased demand for the usage of digital techniques in aircraft. MIL-STD-1553B is widely referred to as an international standard for military applications. The MIL-STD-1553B protocol is implemented using chipsets which are mostly manufactured by companies outside India. In this project, we have created a simulator that behaves just like the physical controller Chipset. The purpose of this project was to create software that could be used to mimic the behavior of the Chipset so that a large amount of test cases could be carried out on the simulator instead of physical hardware. The project was built using C++.

Design, fabrication and experimental analysis of piezoresistive bidirectional acoustic sensor

PurposeIdentification of the direction of the sound source is very important for human–machine interfacing in the applications such as target detection on military applications and wildlife conservation. Considering its vast applications, this study aims to design, simulate, fabricate and test a bidirectional acoustic sensor having two cantilever structures coated with piezoresistive material for sensing has been designed, simulated, fabricated and tested.Design/methodology/approachThe structure is a piezoresistive acoustic pressure sensor, which consists of two Kapton diaphragms with four piezoresistors arranged in Wheatstone bridge arrangement. The applied acoustic pressure causes diaphragm deflection and stress in diaphragm hinge, which is sensed by the piezoresistors positioned on the diaphragm. The piezoresistive material such as carbon or graphene is deposited at maximum stress area. Furthermore, the Wheatstone bridge arrangement has been formed to sense the change in resistance resulting into imbalanced bridge and two cantilever structures add directional properties to the acoustic sensor. The structure is designed, fabricated and tested and the dimensions of the structure are chosen to enable ease of fabrication without clean room facilities. This structure is tested with static and dynamic calibration for variation in resistance leading to bridge output voltage variation and directional properties.FindingsThis paper provides the experimental results that indicate sensor output variation in terms of a Wheatstone bridge output voltage from 0.45 V to 1.618 V for a variation in pressure from 0.59 mbar to 100 mbar. The device is also tested for directionality using vibration source and was found to respond as per the design.Research limitations/implicationsThe fabricated devices could not be tested for practical acoustic sources due to lack of facilities. They have been tested for a vibration source in place of acoustic source.Practical implicationsThe piezoresistive bidirectional sensor can be used for detection of direction of the sound source.Social implicationsIn defense applications, it is important to detect the direction of the acoustic signal. This sensor is suited for such applications.Originality/valueThe present paper discusses a novel yet simple design of a cantilever beam-based bidirectional acoustic pressure sensor. This sensor fabrication does not require sophisticated cleanroom for fabrication and characterization facility for testing. The fabricated device has good repeatability and is able to detect the direction of the acoustic source in external environment.

R-LRBPNet: A Lightweight SAR Image Oriented Ship Detection and Classification Method

Synthetic Aperture Radar (SAR) has the advantage of continuous observation throughout the day and in all weather conditions, and is used in a wide range of military and civil applications. Among these, the detection of ships at sea is an important research topic. Ships in SAR images are characterized by dense alignment, an arbitrary orientation and multiple scales. The existing detection algorithms are unable to solve these problems effectively. To address these issues, A YOLOV8-based oriented ship detection and classification method using SAR imaging with lightweight receptor field feature convolution, bottleneck transformers and a probabilistic intersection-over-union network (R-LRBPNet) is proposed in this paper. First, a CSP bottleneck with two bottleneck transformer (C2fBT) modules based on bottleneck transformers is proposed; this is an improved feature fusion module that integrates the global spatial features of bottleneck transformers and the rich channel features of C2f. This effectively reduces the negative impact of densely arranged scenarios. Second, we propose an angle decoupling module. This module uses probabilistic intersection-over-union (ProbIoU) and distribution focal loss (DFL) methods to compute the rotated intersection-over-union (RIoU), which effectively alleviates the problem of angle regression and the imbalance between angle regression and other regression tasks. Third, the lightweight receptive field feature convolution (LRFConv) is designed to replace the conventional convolution in the neck. This module can dynamically adjust the receptive field according to the target scale and calculate the feature pixel weights based on the input feature map. Through this module, the network can efficiently extract details and important information about ships to improve the classification performance of the ship. We conducted extensive experiments on the complex scene SAR dataset SRSDD and SSDD+. The experimental results show that R-LRBPNet has only 6.8 MB of model memory, which can achieve 78.2% detection accuracy, 64.2% recall, a 70.51 F1-Score and 71.85% mAP on the SRSDD dataset.

Analysis of truncated structure flexible microstrip patch antenna on jute substrate for biomedical applications

In the present years, academic and scientific societies have given more attention to flexible technology. When antenna performance is very poor due to its surrounding environment, flexible antennas have become important. A flexible patch antenna is presented using a Jute fiber with improved performance. It is designed with jute substrate material and a copper conducting layer for ground and patch. A rectangular stripped structure has been used in the antenna for enhancing the parameters and optimisations. The antenna is designed at a resonating frequency of 2.45 GHz. The efficiency of the antenna is measured from return loss, directivity and gain. It can be used for military applications, ground radar position, search and rescue applications. It is capable of biomedical application due to its minimised SAR value. It is used due to its inexpensive cost and abundant availability of jute substrate.

A weight induced contrast map for infrared and visible image fusion

Fusion involves merging details from both infrared (IR) and visible images to generate a unified composite image that offers richer and more valuable information than either individual image. Surveillance, navigation, remote sensing, and military applications require various imaging modalities, including visible and IR, to oversee specific scenes. These sensors provide supplementary data and improve situational understanding, so it is essential to fuse this information into a single image. Fusing IR and visible images presents several challenges due to the differences in imaging modalities, data characteristics, and the need for accurate and meaningful integration of information. In this context, a novel image fusion architecture focuses on enhancing prominent targets, with the objective of integrating thermal information from infrared images into visible images while preserving textural details within the visible images. Initially, in the proposed algorithm, the images from different sensors are divided into components of high and low frequencies using a Guided filter and an Average filter, respectively. A unique contrast detection mechanism is proposed that is capable of preserving the contrast information from the original images. Further, the contrast details of the IR and visible images are enhanced using local standard deviation filtering and local range filtering, respectively. We have developed a new weight map construction strategy that can effectively preserve the supplemental data from both the original images. These weights and gradient details of the source images are utilized to preserve the salient feature details of the images acquired from the various modalities. A decision-making approach is utilized among the high-frequency components of the original images to retain the prominent feature details of the source images. Finally, the salient feature details and the prominent feature details are integrated to generate the fused image. The developed technique is validated using both subjective and quantitative perspectives. The developed approaches provide EN, MI, Nabf, and SD of 6.86815, 13.73269, 0.15390, and 78.16158 respectively against deep learning-based approaches. Also, the proposed algorithm provides EN, MI, Nabf, FMIw, and Qabf against 6.86815, 13.73269, 0.15390, 0.41634 and 0.47196 respectively against existing traditional fusion methods. It is observed that the developed technique provides adequate accuracy against twenty-seven state-of-the-art techniques.

Anti-Offset Multicoil Underwater Wireless Power Transfer Based on a BP Neural Network

Autonomous underwater vehicles (AUVs) are now widely used in both civilian and military applications; however, wireless charging underwater often faces difficulties such as disturbances from ocean currents and errors in device positioning, making proper alignment of the charging devices challenging. Misalignment between the primary and secondary coils can significantly impact the efficiency and power of the wireless charging system energy transfer. To address the issue of misalignment in wireless charging systems, this paper proposes a multiple transfer coil wireless power transfer (MTCWPT) system based on backpropagation (BP) neural network control combined with nonsingular terminal sliding mode control (NTSMC) to enhance further the system robustness and efficiency. To achieve WPT in the ocean, a coil shielding case structure was equipped. In displacement experiments, the proposed multi-transmitting coil system could achieve stable power transfer of 40 W and efficiency of over 78.5% within a displacement range of 8 cm. The system robustness was also validated. This paper presents a new AUV energy supply solution based on MTCWPT. The proposed MTCWPT system can significantly improve the navigation performance of AUVs.

Secure deep learning-based energy efficient routing with intrusion detection system for wireless sensor networks

In general, wireless sensor networks are used in various industries, including environmental monitoring, military applications, and queue tracking. To support vital applications, it is crucial to ensure effectiveness and security. To prolong the network lifetime, most current works either introduce energy-preserving and dynamic clustering strategies to maintain the optimal energy level or attempt to address intrusion detection to fix attacks. In addition, some strategies use routing algorithms to secure the network from one or two attacks to meet this requirement, but many fewer solutions can withstand multiple types of attacks. So, this paper proposes a secure deep learning-based energy-efficient routing (SDLEER) mechanism for WSNs that comes with an intrusion detection system for detecting attacks in the network. The proposed system overcomes the existing solutions’ drawbacks by including energy-efficient intrusion detection and prevention mechanisms in a single network. The system transfers the network’s data in an energy-aware manner and detects various kinds of network attacks in WSNs. The proposed system mainly comprises two phases, such as optimal cluster-based energy-aware routing and deep learning-based intrusion detection system. Initially, the cluster of sensor nodes is formed using the density peak k-mean clustering algorithm. After that, the proposed system applies an improved pelican optimization approach to select the cluster heads optimally. The data are transmitted to the base station via the chosen optimal cluster heads. Next, in the attack detection phase, the preprocessing operations, such as missing value imputation and normalization, are done on the gathered dataset. Next, the proposed system applies principal component analysis to reduce the dimensionality of the dataset. Finally, intrusion classification is performed by Smish activation included recurrent neural networks. The proposed system uses the NSL-KDD dataset to train and test it. The proposed one consumes a minimum energy of 49.67 mJ, achieves a better delivery rate of 99.92%, takes less lifetime of 5902 rounds, 0.057 s delay, and achieves a higher throughput of 0.99 Mbps when considering a maximum of 500 nodes in the network. Also, the proposed one achieves 99.76% accuracy for the intrusion detection. Thus, the simulation outcomes prove the superiority of the proposed SDLEER system over the existing schemes for routing and attack detection.

Qualifying the cathode aging process for storage life prediction for primary AgO-Zn batteries

AgO-Zn batteries are widely recognized for their high energy density, specific capacity, and safety features. Especially the AgO-Zn reserve battery, which possesses good storage stability to better adapt to the application requirements of long-term storage, is considered an ideal candidate for applications in military, aerospace, and other fields. However, since there are only a few studies on the decomposition kinetic of the cathode for the AgO-Zn reserve battery, further in-depth research is needed on the aging mechanism. Herein, we conduct a comprehensive investigation of the aging behavior of the cathode in commercial AgO-Zn reserve batteries. The physicochemical properties of the cathodes with different storage years are characterized by multiple methods, including phase composition, surface morphology, and thermal behaviors. The evolution of structure and performance for the cathodes with storage time and their impact on the electrical performance of AgO-Zn batteries are studied. In addition, a multiple heating rate method is performed to determine the thermal decomposition kinetics of the cathode. Based on the obtained kinetic parameters, a model for the decomposition of the AgO in the cathode is developed, enabling the estimation of theoretical storage time for achieving the cathode with the same retention rate as actual storage in a shortened time by accelerated aging. Validation studies comparing accelerated aging results with real-time aging under natural conditions are further performed to assess the reliability of the accelerated aging model. This research provides insights into the aging mechanisms of cathode for AgO-Zn batteries and offers a systematic approach for the accelerated aging test, paving the way for the development of the prediction of battery performance and lifespan.