Satellite Technology Research Articles

Generation of PM10 Map with Sentinel-2 Satellite Images: The Case of Çankırı Province

Air pollution, which is characterized as a global environmental problem, negatively affects life in Turkey as a result of the increase in the amount of energy needed and uncontrolled construction. In order to minimize the health impacts of air pollution, air quality should be monitored regularly and necessary steps should be taken to improve it. With the innovations in satellite technologies, the air quality of large areas can be monitored with the help of satellite images and effective solutions can be produced in many areas such as the detection of air pollutant parameters and the creation of thematic maps. The main objective of the research is to investigate the relationship between in-situ measured PM10 parameters and Sentinel-2 satellite data and to map PM10 based on this relationship. In this context, PM10 parameters measured in the field on two different dates and Sentinel-2 satellite images dated 22.11.2021 and 16.04.2022 were used as data sources. The relationship between the data used was established by multiple regression analysis. The coefficients obtained from the analysis results were applied to the relevant bands and thematic maps were created using satellite images. The correlation coefficients of 0.80 and 0.79 calculated by regression analyses indicate that sufficient accuracy was achieved in the research. The results of the study show that satellite imagery provides accurate data for PM10 estimate and that pollution exceeds World Health Organization limits in the road transportation network and industrial areas.

An intelligent load balancing algorithm for 5G‐satellite networks

SummaryCellular networks are projected to deal with an immense rise in data traffic, as well as an enormous and diverse device, plus advanced use cases, in the nearest future; hence, future 5G networks are being developed to consist of not only 5G but also different radio access technologies (RATs) integrated. In addition to 5G, the user's device (UD) will be able to connect to the network via LTE, WiMAX, WiFi, Satellite and other technologies. On the other hand, Satellite has been suggested as a preferred network to support 5G use cases. However, achieving load balancing is essential to guarantee an equal amount of traffic distributed between different RATs in a heterogeneous wireless network; this would enable optimal utilisation of the radio resources and lower the likelihood of call blocking/dropping. This study presented an artificial intelligent‐based application in heterogeneous wireless networks and proposed an enhanced particle optimisation (EPSO) algorithm to solve the load balancing problem in 5G‐Satellite networks. The algorithm uses a call admission control strategy to admit users into the network to ensure that users are evenly distributed on the network. The proposed algorithm was compared with the Artificial Bee Colony and Simulated Annealing algorithm using three performance metrics: throughput, call blocking and fairness. Finally, based on the experimental findings, results outcomes were analysed and discussed.

Satellite wave 2D spectrum partition based on the PI-vit-GAN(physically-informed ViT-GAN) method

The abundant spectral data provided by satellite technology are crucial for interpreting the complex marine environment, and the effective and accurate analysis of these data is particularly important for coastal engineering. In this regard, this study proposes a Physically Informed ViT-GAN (PI-ViT-GAN) automatic partitioning method, based on CFOSAT satellite wave spectrum data. Specifically, the model consists of a generator and discriminator. The generator utilizes a contrastive learning strategy as pretraining and through the self-attention mechanism of the ViT model, it focuses on key parts of the spectrum to extract wave group features and wave element parameters. Partitioning-head joint training realizes the output of wave group partition element indices. Subsequently, the discriminator uses the wave group features and a parametric model for spectrum reconstruction and computes the error with the original observed spectrum to evaluate the partition and reconstruction effects. Additionally, this model incorporates two physically corrected functions, wave system classification loss and merging loss, based on the wave age criterion, thereby guiding the training process, and enhancing model efficiency. The results indicate that the reconstructed theoretical spectrum, obtained through the utilization of this method, aligns well with the original sea wave spectrum, demonstrating a precision superior to the spectral partitioning product of CFOSAT's own SWIM. Combining the robust learning capability of the transformer and the regularization of physical prior knowledge, this model can achieve precise, low-cost automated analysis of satellite wave spectra, providing a new scalable method for big data analysis in marine and coastal engineering.

Design of Onboard Avionics Based on Commercial Off-the-Shelf Parts for TianQi-2 Nanosatellite

With the development of modern small satellite technology, short development cycles, low cost, and high reliability have become trends in the era of New Space. To achieve the above goals, an integrated centralized architecture of onboard avionics for an internet of things CubeSat was proposed, and CAN, I2C, and 1-wire buses were employed for telemetry collection and command sending. The implementation of onboard computers (OBCs) and the power conditioning and distribution unit (PCDU) was introduced based on the PC104 industrial standards. An arbitration switching strategy between the primary and backup OBCs was proposed so that the primary OBC had priority to be on duty. Over 98% of commercial off-the-shelf (COTS) parts were used to decrease costs, so a procedure for COTS part selection and a qualified method were presented for reliable application. The onboard avionics, including OBC and PCDU, were developed in six months, and the satellite has been in orbit for more than three years and still works well. The reliability of the onboard avionics developed using the philosophy of New Space is demonstrated by the three-year flight in orbit.

Article: View on Regulations Concerning Communication, Navigation and Surveillance (CNS) Service in Civil Aviation

This article presents the overall regulatory environment related to the provision of Communication, Navigation and Surveillance (CNS) services in civil aviation. Through the evolution of international standards established by the Chicago Convention and through the development of CNS services, insight was given into the importance ofCNSservices in ensuring safe and efficient air traffic.The functions of the CNS system are presented and explained, as well as the key contribution of international organizations such as ICAO and International Telecommination Union (ITU) in the development of these services. Through research on the complexity of CNS services, the evolution in the past decades, the text explains the legal aspects related to civil aviation, but also international telecommunications and space activities that are related to civil aviation. The legal framework that regulates space activities, that is, the use of satellites in air traffic management, is especially covered. airspace (CNS/ATM). ICAO initiatives are additionally addressed, particularly the integration of satellite technology through Future Air Navigation Systems (FANS) and the legal significance of resolutions such as A32-19 on Global Navigation Satellite System (GNSS) services from the 1998 Rio Conference. The narrative further examines the implementation of CNS/ATM concepts, legal considerations in air-ground communications, harmonization efforts, and the consolidation of resolutions for effective global implementation. The text concludes by highlighting ICAO’s ongoing commitment to align technological advancements with legal frameworks, promoting the seamless utilization of CNS/ATM systems worldwide. The significance of regional and national regulations, with a focus on European CNS regulations, is underscored for enhancing air traffic safety and fostering the development of CNS services. CNS Services, Chicago Convention, ICAO international standards, Annex 10, ICAO resolutions, CNS/ATM, ITU, FANS, GNSS, regional and national regulations

Models, simulations, and applications of small satellite thermal analysis

Progress in satellite technology places higher expectations on the design period and reliability of thermal control systems, especially for small satellites with high intensification. Here, a thermal analysis is conducted throughout the satellite development process, with thermal modeling serving as the foundation for thermal analysis in the early and formal design and test verification stages. As a result, designers are required to appreciate, penetrate, and properly apply thermal models for the development of satellite thermal systems. Thus, in this article, we reviewed the research and development of thermal model techniques, as well as the preparation of crucial parameters and means of simplification for accurate and fast solutions. In addition, a summary of the relevant application and state-of-the-art technologies such as uncertainty and sensitivity analysis, intelligent optimization design, and parameter correlation, was dedicated to promoting the comprehensive development and innovation of thermal analysis of satellites.

Examining Spatiotemporal Photosynthetic Vegetation Trends in Djibouti Using Fractional Cover Metrics in the Digital Earth Africa Open Data Cube

The Horn of Africa has sensitive, arid ecosystems, with its vegetation commonly distressed by factors such as climate change, population increase, unstable water resources, and rarely enforced land use management practices. These factors make countries such as Djibouti highly variable locations for the growth of vegetation and agricultural products, and these countries are becoming more vulnerable to food insecurity as the climate warms. The rapid growth of satellite and digital image processing technology over the last five decades has improved our ability to track long-term agricultural and vegetation changes. Data cubes are a newer approach to managing satellite imagery and studying temporal patterns. Here, we use the cloud-based Digital Earth Africa, Open Data Cube to analyze 30 years of Landsat imagery and orthomosaics. We analyze long-term trends in vegetation dynamics by comparing annual fractional cover metrics (photosynthetic vegetation, non-photosynthetic vegetation, and bare ground) to the Normalized Difference Vegetation Index. Investigating Djibouti-wide and regional vegetation trends, we provide a comparison of trends between districts and highlight a primary agricultural region in the southeast as a detailed example of vegetation change. The results of the Sen’s slope and Mann–Kendall regression analyses of the data cube suggest a significant decline in vegetation (p = 0.00002), equating to a loss of ~0.09 km2 of arable land per year (roughly 2.7 km2 over the 30-year period). Overall, decreases in photosynthetic vegetation and increases in both non-photosynthetic vegetation and bare soil areas indicate that the region is becoming more arid and that land cover is responding to this trend.

True Research on Super Artificial Intelligence Computer Based Satellite Deep Tech Artificial Telepathic, Neurotechnology or Mind Controller and Wireless Direct Energy Weapon, Psychotronic Cyber Crime Technologies

Wireless Remote Neural Monitoring: Bridging the Gap between Brain and Technology In the field of Neuroscience and technological advancements, the concept of Deep Tech Satellite Wireless Neural Monitoring technology has emerged as a ground breaking innovation. Which has been developed to read and understand the human brain and interact with it, which is also a wireless Direct Energy weapon. These Satellite Surveillance Criminal Operators are using this Wireless Psychotronic Neuro technology on a large scale against citizens.. Cyber criminals have started taking the help of technologies like Deep tech, satellite wireless Artificial Telepathy technology and wireless Neuro technology Bio Electro Magnetic Weapon. This is illegal deep tech satellite Neuro technology Or Mind controller technology and synthetic telepathic technology which is a psychotronic weapon and Hypnotic technology. These are deep tech satellite technologies that are used to harm and control citizens from a distance. Microwave hearing, also known as Voice to Skull [V2K]. This is Brain manipulation and Silent weapon satellite technology. This Satellite Super Artificial Intelligence [AI] Computer Or Super Computer is a Big Engineering. It is also a satellite surveillance Direct Energy weapon [Non-Contact Weapon]and Radiation weapon with which these Satellite Surveillance criminal operators carry out Physical and Cyber-attacks on citizens. Satellite Surveillance criminal operators and Cyber criminals do business worth several trillion dollars through this illegal satellite deep tech technology. This true research has been done to protect citizens from illegal deep tech satellite surveillance technology and Cyber terrorism.

THE EVOLUTION OF QUALITY ASSURANCE AND SERVICE IMPROVEMENT IN SATELLITE TELECOMMUNICATIONS THROUGH ANALYTICS: A REVIEW OF INITIATIVES AND THEIR IMPACTS

Satellite telecommunications have undergone significant evolution, driven by the need for enhanced quality assurance and service improvement. This paper provides a comprehensive review of the initiatives undertaken in this field, focusing on the integration of analytics to achieve these objectives. Over the years, advancements in satellite technology have enabled the collection of vast amounts of data, presenting both challenges and opportunities. Leveraging analytics has emerged as a crucial strategy to extract actionable insights from this data, thereby enhancing quality assurance and service delivery. The review encompasses various aspects of quality assurance and service improvement in satellite telecommunications, including network performance monitoring, fault detection and resolution, capacity planning, and customer experience management. It examines how analytics techniques such as machine learning, predictive modeling, and anomaly detection have been applied to address specific challenges within each of these domains. Furthermore, the paper evaluates the impacts of these initiatives on the satellite telecommunications industry. By leveraging analytics, stakeholders have been able to optimize network operations, minimize downtime, and proactively address potential issues before they escalate. Additionally, improved service quality has led to enhanced customer satisfaction and retention, driving business growth and competitiveness in the market. Overall, this review underscores the transformative role of analytics in advancing quality assurance and service improvement in satellite telecommunications. It highlights the importance of continued innovation and investment in analytics-driven solutions to meet the evolving demands of the industry and deliver superior experiences to end-users.
 Keywords: Assurance, Analytics, Satellite, Telecommunication, Impacts, Review.

SUSTAINABLE BUSINESS MODELS IN SATELLITE TELECOMMUNICATIONS

Sustainable business models in satellite telecommunications represent a critical paradigm shift in the industry, integrating environmental, social, and economic dimensions into operations. This review explores the evolving landscape of sustainable practices within satellite telecommunications, addressing the pressing need for eco-conscious strategies in an era of accelerating technological advancement. The burgeoning demand for satellite telecommunications services, driven by global connectivity needs, underscores the significance of sustainability in the industry. Traditional business models have often prioritized profit margins over environmental and social impacts. However, emerging trends emphasize the adoption of sustainable practices to mitigate carbon footprints, reduce electronic waste, and promote equitable access to communication services. Innovations in satellite technology, such as the development of small satellites and advancements in propulsion systems, offer opportunities to enhance sustainability. Miniaturization of satellites decreases launch mass, leading to reduced fuel consumption and lower emissions. Additionally, advancements in electric propulsion systems contribute to fuel efficiency and prolong satellite lifespan, thereby reducing space debris. Furthermore, sustainable business models in satellite telecommunications encompass social responsibility initiatives aimed at bridging the digital divide. Collaborative efforts between satellite operators, governments, and non-profit organizations facilitate the provision of affordable and accessible connectivity to underserved regions, fostering socio-economic development and empowering marginalized communities. The integration of sustainability into satellite telecommunications business models not only aligns with environmental and social imperatives but also presents economic benefits. Cost efficiencies realized through fuel savings, extended satellite lifespan, and market expansion in underserved regions enhance long-term profitability and resilience in a competitive industry landscape. The transition towards sustainable business models in satellite telecommunications represents a pivotal evolution towards a more responsible and inclusive industry, balancing profitability with environmental stewardship and social equity.
 Keywords: Business, Models, Satellite, Telecommunication, Sustainable, Review.

Survey of IP-based air-to-ground data link communication technologies

The main purpose of an air traffic management system is to provide air traffic services to an aircraft moving within the controlled airspace. Very high frequency (VHF) radio in continental regions, as well as high frequency (HF) radio and satellite communications in remote areas, are used today as the primary way of delivering air traffic services. The technical limitations and constraints associated with the current technology, such as line-of-sight requirement, vulnerability to interference, and limited coverage, cause degraded voice quality and discontinuity in service. At the same time, voice-based communication may affect flight safety due to poor language skills, call sign confusion, and failure to use standard phraseology. For this reason, text-based communication over a VHF data link (VDL) has been proposed as an alternative. However, it is predicted that VDL will be insufficient to support increasing air traffic and intensive data exchanges due to its lack of mobility support and limited resources to ensure service continuity. This paper surveys next-generation data link technologies based on the current state of the "industry standard" for aeronautical communication. These include Aeronautical Mobile Airport Communication System (AeroMACS), L-band Digital Aeronautical Communications System (LDACS), and Airborne New Advanced Satellite Techniques & Technologies in a System Integrated Approach (ANASTASIA). The paper also surveys IP-based text communication solutions over these next-generation data links. We analyze the efficiency of the proposed solutions with regard to service continuity and aeronautical application requirements. We conclude the survey by identifying open problems and future trends.

Spatio-temporal evaluation of air pollution using ground-based and satellite data during COVID-19 in Ecuador

The concentration of gases in the atmosphere is a topic of growing concern due to its effects on health, ecosystems etc. Its monitoring is commonly carried out through ground stations which offer high precision and temporal resolution. However, in countries with few stations, such as Ecuador, these data fail to adequately describe the spatial variability of pollutant concentrations. Remote sensing data have great potential to solve this complication. This study evaluates the spatiotemporal distribution of nitrogen dioxide (NO2) and ozone (O3) concentrations in Quito and Cuenca, using data obtained from ground-based and Sentinel-5 Precursor mission sources during the years 2019 and 2020. Moreover, a Linear Regression Model (LRM) was employed to analyze the correlation between ground-based and satellite datasets, revealing positive associations for O3 (R2 = 0.83, RMSE = 0.18) and NO2 (R2 = 0.83, RMSE = 0.25) in Quito; and O3 (R2 = 0.74, RMSE = 0.23) and NO2, (R2 = 0.73, RMSE = 0.23) for Cuenca. The agreement between ground-based and satellite datasets was analyzed by employing the intra-class correlation coefficient (ICC), reflecting good agreement between them (ICC ≥0.57); and using Bland and Altman coefficients, which showed low bias and that more than 95% of the differences are within the limits of agreement. Furthermore, the study investigated the impact of COVID-19 pandemic-related restrictions, such as social distancing and isolation, on atmospheric conditions. This was categorized into three periods for 2019 and 2020: before (from January 1st to March 15th), during (from March 16th to May 17th), and after (from March 18th to December 31st). A 51% decrease in NO2 concentrations was recorded for Cuenca, while Quito experienced a 14.7% decrease. The tropospheric column decreased by 27.3% in Cuenca and 15.1% in Quito. O3 showed an increasing trend, with tropospheric concentrations rising by 0.42% and 0.11% for Cuenca and Quito respectively, while the concentration in Cuenca decreased by 14.4%. Quito experienced an increase of 10.5%. Finally, the reduction of chemical species in the atmosphere as a consequence of mobility restrictions is highlighted. This study compared satellite and ground station data for NO2 and O3 concentrations. Despite differing units preventing data validation, it verified the Sentinel-5P satellite's effectiveness in anomaly detection. Our research's value lies in its applicability to developing countries, which may lack extensive monitoring networks, demonstrating the potential use of satellite technology in urban planning.

Real growth in space manufacturing output substantially exceeds growth in the overall space economy

Accurately measuring real economic output in the space economy is made difficult by the rapid increase in capabilities and decrease in prices of launch and satellite technologies achieved over the past two decades. Nominal measures of output in space will tend to underestimate real growth if customers are paying lower prices for better services over time. In this paper, we use price indexes that apply techniques to the space economy that have been used for decades to adjust nominal measures of output in sectors such as information technology, including matched-model and explicit hedonic quality adjustment. We find that adjusting for price and quality changes in the space economy has substantial effects on estimated growth in economic output, especially across its sectors. Price increases over time in the space information sector, which is dominated by direct-to-home (DTH) satellite television, mean that real growth has been slower than nominal growth since at least 2012, the typical pattern in industries not undergoing rapid technological change. In sharp contrast, rapid price decreases and quality increases in other areas—especially launch and manufacturing of satellite, earth observation, and positioning, navigation, and timing (PNT) equipment—have meant that nominal growth rates substantially understate real growth rates in those industries. Given the central importance of space to our modern economy, having accurate information on growth in the space economy is vital for efficiently allocating the substantial private and public investment being devoted to its development.

STRATEGIC PARTNERSHIPS IN THE SATELLITE AND TELECOMMUNICATIONS SECTORS: A CONCEPTUAL REVIEW OF DATA ANALYTICS-ENABLED IDENTIFICATION AND CAPITALIZATION OF SYNERGIES

Strategic partnerships in the satellite and telecommunications sectors have become increasingly vital as technological advancements and market complexities continue to evolve. This conceptual review delves into the significance of data analytics-enabled identification and capitalization of synergies within these partnerships. The fusion of satellite and telecommunications technologies presents unique opportunities for innovation and growth, but also challenges that necessitate strategic collaboration. By leveraging data analytics, organizations can effectively identify synergies between satellite and telecommunications services, leading to enhanced operational efficiencies, expanded service offerings, and improved customer experiences. Through a comprehensive analysis of available data, companies can pinpoint areas of overlap and complementary strengths, laying the foundation for mutually beneficial partnerships. The review explores the multifaceted nature of strategic partnerships in these sectors, emphasizing the importance of aligning technological capabilities, market strategies, and regulatory frameworks. It underscores the role of data analytics as a catalyst for informed decision-making, enabling stakeholders to anticipate market trends, optimize resource allocation, and mitigate risks. Furthermore, the review examines the implications of emerging technologies such as artificial intelligence, machine learning, and predictive analytics on partnership dynamics. These tools not only streamline data analysis processes but also empower organizations to proactively identify synergistic opportunities and adapt to evolving market dynamics in real-time. Through a synthesis of theoretical frameworks and empirical evidence, this review provides insights into the strategic imperatives guiding partnership formation and management in the satellite and telecommunications sectors. It underscores the need for a holistic approach that integrates technological expertise with business acumen and regulatory compliance to unlock the full potential of strategic collaborations. The review advocates for a proactive and data-driven approach to identifying and capitalizing on synergies within strategic partnerships in the satellite and telecommunications sectors. By harnessing the power of data analytics, organizations can navigate the complexities of the digital ecosystem, drive innovation, and achieve sustainable competitive advantage in an increasingly interconnected world.
 Keywords: Partnership, Telecommunication, Data Analytics, Capitalization, Enabled Identification, Review.

Women Safety Device Using IOT

Abstract - Addressing the safety concerns of women in society is a critical issue, and the application of technology offers a promising avenue to enhance their protection. A prime example of this technological application is the deployment of a GPS-based safety mechanism. This system, specifically designed for the assistance of women, features a GPS module capable of tracking the user's location. In emergency situations, the device quickly alerts a preselected emergency contact. Users can activate the system either through a smartphone application or by pressing a dedicated button on the device itself. Through the use of satellite technology, the GPS module in the device precisely locates the user and facilitates communication, ensuring timely assistance when needed. Keywords—At mega 328, GPS, GSM Module, Wi-Fi Controller

A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations

Climate change is profoundly affecting the global water cycle, increasing the likelihood and severity of extreme water-related events. Better decision-support systems are vital to accurately predict and monitor water-related environmental disasters and optimally manage water resources. These must integrate advances in remote sensing, in situ, and citizen observations with high-resolution Earth system modeling, artificial intelligence (AI), information and communication technologies, and high-performance computing. Digital Twin Earth (DTE) models are a ground-breaking solution offering digital replicas to monitor and simulate Earth processes with unprecedented spatiotemporal resolution. Advances in Earth observation (EO) satellite technology are pivotal, and here we provide a roadmap for the exploitation of these methods in a DTE for hydrology. The 4-dimensional DTE Hydrology datacube now fuses high-resolution EO data and advanced modeling of soil moisture, precipitation, evaporation, and river discharge, and here we report the latest validation data in the Mediterranean Basin. This system can now be explored to forecast flooding and landslides and to manage irrigation for precision agriculture. Large-scale implementation of such methods will require further advances to assess high-resolution products across different regions and climates; create and integrate compatible multidimensional datacubes, EO data retrieval algorithms, and models that are suitable across multiple scales; manage uncertainty both in EO data and models; enhance computational capacity via an interoperable, cloud-based processing environment embodying open data principles; and harness AI/machine learning. We outline how various planned satellite missions will further facilitate a DTE for hydrology toward global benefit if the scientific and technological challenges we identify are addressed.

Two split rings resonator-based perfect metamaterial absorbers with the incident and polarization angle independent for sensing applications

The perfect metamaterial absorber (PMA) optimized for high-performance absorbers to find the multiple sensing application. The structural composition of the PMA consists of two split ring resonators with six split gaps configured in an exhibit symmetry of rotation. The fundamental component of the design has three distinct layers: (1) the top and bottom layers, composed of a metallic substance with copper dielectric substrate with a thickness of 0.035 mm that exhibits lossy metal; (2) the middle layer, made of a lossy dielectric material referred to as Rogers RT5870 dielectric substrate with a thickness of 1.575 mm. The findings reveal that the absorber achieves a broad absorption spectrum, with simulated results from the CST Microwave Studio simulator indicating absorption peaks at 5.88, 9.20, and 15.88 GHz. whereas the strong absorbance is 99.91, 99.99, and 99.97 % with a good quality factor (Q) 29.40, 9.20, 13.23, respectively. The structural dimensions (7 × 7 mm2) are designed to deliver remarkable performance. The tri-band PMA exhibits polarization independent at various angles, including 0, 45, 90, 135, and 180° for both transverse magnetic (TM) and transverse electric (TE) modes. It has excellent absorption capabilities across multiple angles of incidence from 0 to 80°, including the whole operational spectrum. A comparative investigation of the circuit indicates the enhanced performance of the PMA, demonstrating its potential for exceptional functionality inside the advanced design system (ADS) software. Furthermore, the structures under consideration, which were simulated using the High-Frequency Structure Simulator (HFSS), demonstrate a strong agreement with the highest level of absorption seen at each resonance peak in the CST simulation outcomes. This paper introduces an alternative protocol, expressed in terms of the TE and TM modes, for use with the restricted symmetric structure to find multiple sensing application. The proposed study highlights the exceptional properties of PMA provides several practical advantages, including its high absorption capacity, in multiple sensing application, insensitivity to incident and polarization angles, satellite technology, raw satellite feeds, and radars owing to these performance features.

A Comprehensive Analysis of Technology in Aeroponics: Presenting the Adoption and Integration of Technology in Sustainable Agriculture Practices

Aeroponics is a soilless farming method in which plants are grown by sprinkling a nutrient-rich fluid over their roots. Aeroponics has changed as a result of technology, which now offers advantages including automated nutrient supply, environmental management, and plant health monitoring. A key area of concern in light of the rising global food demand, climate change, and environmental issues is sustainable agriculture. This article highlights the integration of technology, sustainability, and socio-economic elements in modern agriculture by methodically examining the development of aeroponics practices from conventional ways to innovative modern techniques. When agronomic practices are viewed historically, they show a shift from labor-intensive, antiquated techniques to precision-based, technology-driven processes. Even though they were sustainable, traditional methods frequently had efficiency and scalability issues. A big change came with the arrival of the Green Revolution, which brought synthetic inputs and high-yield crop varieties. However, a reevaluation towards more sustainable practices was spurred by the approaches' long-term ecological implications. Precision agriculture, which makes use of sensor-based monitoring systems, artificial intelligence (AI), satellite and drone technologies, is a major feature of modern agronomy breakthroughs. According to the systematic research, Industry 4.0 and sensor technology are the most often used technologies in aeroponics. Numerous advantages, including time efficiency and sustainability, have come from these technologies. On the other hand, the research focused on power dependence and technical complexity as the primary obstacles in technology-assisted aeroponics.

Deep Learning-Based Weed–Crop Recognition for Smart Agricultural Equipment: A Review

Weeds and crops engage in a relentless battle for the same resources, leading to potential reductions in crop yields and increased agricultural costs. Traditional methods of weed control, such as heavy herbicide use, come with the drawback of promoting weed resistance and environmental pollution. As the demand for pollution-free and organic agricultural products rises, there is a pressing need for innovative solutions. The emergence of smart agricultural equipment, including intelligent robots, unmanned aerial vehicles and satellite technology, proves to be pivotal in addressing weed-related challenges. The effectiveness of smart agricultural equipment, however, hinges on accurate detection, a task influenced by various factors, like growth stages, environmental conditions and shading. To achieve precise crop identification, it is essential to employ suitable sensors and optimized algorithms. Deep learning plays a crucial role in enhancing weed recognition accuracy. This advancement enables targeted actions such as minimal pesticide spraying or precise laser excision of weeds, effectively reducing the overall cost of agricultural production. This paper provides a thorough overview of the application of deep learning for crop and weed recognition in smart agricultural equipment. Starting with an overview of intelligent agricultural tools, sensors and identification algorithms, the discussion delves into instructive examples, showcasing the technology’s prowess in distinguishing between weeds and crops. The narrative highlights recent breakthroughs in automated technologies for precision plant identification while acknowledging existing challenges and proposing prospects. By marrying cutting-edge technology with sustainable agricultural practices, the adoption of intelligent equipment presents a promising path toward efficient and eco-friendly weed management in modern agriculture.

Remote Sensing Micro-Object Detection under Global and Local Attention Mechanism

With the rapid advancement of technology, satellite and drone technologies have had significant impacts on various fields, creating both opportunities and challenges. In areas like the military, urban planning, and environmental monitoring, the application of remote sensing technology is paramount. However, due to the unique characteristics of remote sensing images, such as high resolution, large-scale scenes, and small, densely packed targets, remote sensing object detection faces numerous technical challenges. Traditional detection methods are inadequate for effectively detecting small targets, rendering the accurate and efficient detection of objects in complex remote sensing images a pressing issue. Current detection techniques fall short in accurately detecting small targets compared to medium and large ones, primarily due to limited feature information, insufficient contextual data, and poor localization capabilities for small targets. In response, we propose an innovative detection method. Unlike previous approaches that often focused solely on either local or contextual information, we introduce a novel Global and Local Attention Mechanism (GAL), providing an in-depth modeling method for input images. Our method integrates fine-grained local feature analysis with global contextual information processing. The local attention concentrates on details and spatial relationships within local windows, enabling the model to recognize intricate details in complex images. Meanwhile, the global attention addresses the entire image’s global information, capturing overarching patterns and structures, thus enhancing the model’s high-level semantic understanding. Ultimately, a specific mechanism fuses local details with global context, allowing the model to consider both aspects for a more precise and comprehensive interpretation of images. Furthermore, we have developed a multi-head prediction module that leverages semantic information at various scales to capture the multi-scale characteristics of remote sensing targets. Adding decoupled prediction heads aims to improve the accuracy and robustness of target detection. Additionally, we have innovatively designed the Ziou loss function, an advanced loss calculation, to enhance the model’s precision in small target localization, thereby boosting its overall performance in small target detection. Experimental results on the Visdrone2019 and DOTA datasets demonstrate that our method significantly surpasses traditional methods in detecting small targets in remote sensing imagery.