Future Technology Trends Research Articles

Energy Microgrids: Exploring Technology Trends and Prospects for Efficient Energy Management

Objective: The objective of this paper is to explore technology trends and prospects for efficient energy management in microgrids by identifying and analyzing distinct research lines in this field. Method: A Scopus search was conducted using keywords such as "microgrids" and "new technologies." The gathered information was processed using Bibliometrix software to cluster the data. This analysis identified five distinct research lines related to microgrids and energy management. Results and Discussion: The analysis revealed five distinct research lines: (1) microgrids related to energy generation and storage, (2) electric power system control, (3) electric power transmission networks, (4) optimization, and (5) power markets. The paper develops and explains these research lines comprehensively, detailing technology trends and prospects for efficient energy management. Additionally, a combined analysis of relevance and development classifies the research lines as either emerging or declining and determines whether they represent basic or motor themes. Research Implications: The findings provide insights into current and future trends in microgrid technology, offering valuable information for researchers, practitioners, and policymakers. Understanding these trends can help guide future research, development, and implementation strategies for efficient energy management in microgrids. Originality/Value: This paper offers a comprehensive analysis of technology trends and prospects in microgrids, utilizing advanced bibliometric tools to identify and classify research lines. The study provides a unique perspective on the development and relevance of different aspects of microgrid technology, contributing valuable insights to the field.

SWOT Analysis of Future Trends in BEV-related Technologies: Xiaomi Automobile Co., Ltd's Latest Product as a Case Study

The new energy vehicle sector has benefited from numerous subsidies in response to the World Environmental Protection Organization's and governments' calls for a reduction in carbon emissions. Battery-electric vehicles (BEVs), the kind of EV with the lowest carbon emissions, have gained popularity in the automotive industry. Using a battery system as a power system not only improves efficiency but also ensures that it does not pollute the environment. Along with other technological advancements like the incorporation of cutting-edge chips in the central controls of the vehicle and latest AI systems, the convenience of BEVs for consumers keeps increasing. This paper introduces the new technology systems included in the latest products launched by Xiaomi, such as the new battery system, smart driving system, and all-round AI system. Then more analyses of the strengths, weaknesses, opportunities, and threats of BEVs in the future with the impact of new technology. The analysis not only raises some of the technical issues that need to be addressed in BEVs today but also points to the crisis that will exist in the BEV market in the future. After analyzing the situation, some recommendations and directions for in-depth research were given. And take Xiaomi's latest BEV product as an example to further do a SWOT analysis of Xiaomi's strategic development into the BEV market.

Analysis on Innovation and Application of Anti-counterfeiting Technology of Printed Matter

This paper deeply focuses on the innovation and application of printed matter anti-counterfeiting technology, through a variety of advanced anti-counterfeiting technology principle, characteristics and rich application examples to carry out a detailed study, a comprehensive and in-depth analysis of its protection of product safety, resolutely prevent counterfeiting and fully maintain market order and other aspects of the key and important role. At the same time, the future development trend of anti-counterfeiting technology and the current severe challenges are deeply discussed, aiming at providing a very valuable and meaningful reference for the in-depth research and practical operation in related fields.

A review on model predictive control strategies for AC motor drives

AbstractIn the past decade, model predictive control (MPC) has been widely used in AC motor drives. Although a series of improved MPC strategies have been proposed, researchers are still seeking more effective solutions for different application backgrounds and application requirements to achieve the goals such as algorithm simplification, weighting factor design, parameter robustness enhancement, current/torque ripple suppression, and so on. In this paper, aiming at the above problems, the MPC strategy and its optimisation technology for AC motor drive system are comprehensively reviewed. Firstly, this paper introduces the classical MPC technology with the permanent magnet synchronous motor drive system fed by two‐level voltage source inverter as the control object. Secondly, this paper introduces and discusses the existing MPC optimisation methods from the aspects of current/torque ripple suppression, algorithm simplification, weight factor design and parameter robustness enhancement. Finally, based on the current industrial development requirements for AC motor drive systems and the research status of MPC optimisation methods in the existing literature, the current challenges and future trends of MPC technology are discussed.

A Review of the Application of Hyperspectral Imaging Technology in Agricultural Crop Economics

China is a large agricultural country, and the crop economy holds an important place in the national economy. The identification of crop diseases and pests, as well as the non-destructive classification of crops, has always been a challenge in agricultural development, hindering the rapid growth of the agricultural economy. Hyperspectral imaging technology combines imaging and spectral techniques, using hyperspectral cameras to acquire raw image data of crops. After correcting and preprocessing the raw image data to obtain the required spectral features, it becomes possible to achieve the rapid non-destructive detection of crop diseases and pests, as well as the non-destructive classification and identification of agricultural products. This paper first provides an overview of the current applications of hyperspectral imaging technology in crops both domestically and internationally. It then summarizes the methods of hyperspectral data acquisition and application scenarios. Subsequently, it organizes the processing of hyperspectral data for crop disease and pest detection and classification, deriving relevant preprocessing and analysis methods for hyperspectral data. Finally, it conducts a detailed analysis of classic cases using hyperspectral imaging technology for detecting crop diseases and pests and non-destructive classification, while also analyzing and summarizing the future development trends of hyperspectral imaging technology in agricultural production. The non-destructive rapid detection and classification technology of hyperspectral imaging can effectively select qualified crops and classify crops of different qualities, ensuring the quality of agricultural products. In conclusion, hyperspectral imaging technology can effectively serve the agricultural economy, making agricultural production more intelligent and holding significant importance for the development of agriculture in China.

Opportunities and Challenges of Digital Transformation in International Business

With the accelerating pace of globalization and the rapid development of information technology, digital transformation has become a key driver for the growth of international business. This paper aims to explore the opportunities and challenges of digital transformation in international business. First, we define the basic concepts of digital transformation and build a related theoretical framework, including the Technology Acceptance Model (TAM) and Innovation Diffusion Theory. Next, we analyze the main opportunities brought by digital transformation to international business, such as market expansion, operational efficiency improvement, enhanced customer experience, and data-driven decision-making. Then, we discuss the challenges faced by international business in the process of digital transformation, including technological barriers, cultural and organizational changes, data security and privacy, as well as regulatory and compliance issues. Finally, we look forward to future technological and market trends and propose strategic recommendations to address challenges and seize opportunities. This paper provides systematic theoretical guidance and practical advice for international business in the digital transformation process, serving as an important reference for companies to formulate digital strategies.

The role of digital transformation in enhancing clean energy startups' success: An analysis of it integration strategies

This review paper explores the pivotal role of digital transformation in enhancing the success of clean energy startups. It delves into how integrating digital technologies such as IoT, AI, big data, and blockchain can foster innovation, improve scalability, and boost operational efficiency. The paper also examines various IT integration strategies, including cloud computing, data analytics, and smart grid technologies, and their implementation models, highlighting the challenges and potential solutions. Additionally, it discusses the impact of digital transformation on market competitiveness and provides strategic recommendations for startups to leverage these technologies effectively. The paper concludes by predicting future trends in digital technologies and outlining policy implications to support the digital transformation of the clean energy sector.

Research Progress on Friction Nanogenerator Technology for Wave Energy Harvesting

The ubiquitous phenomenon of friction-generated energy, often considered to be of little practical value, has led to the development of a new technology known as friction nanogenerators (FNGs). This innovative technology offers significant potential for the sustained power supply and large-scale harvesting of wave energy, which can be particularly beneficial for ocean sensors. This paper presents an analysis of the current development of FNGs, a detailed description of the principles, operations, and modes of operation of FNGs for wave energy capture, and an investigation of the various FNG structures and their research progress. Additionally, it explores the current challenges and future trends of FNG technology and proposes the integration of FNG technology with other technological fields to provide researchers with a comprehensive understanding of its current status and potential in the field of wave energy harvesting.

Reseña del uso del lenguaje de programación Python en el Desarrollo de Software

Introduction: This article provides a concise and clear definition of the Python programming language, highlighting its key features and its significance in the current landscape of software development. Python, renowned for its simple and readable syntax, has gained popularity due to its versatility and ease of use. Objective: The primary objective of this study is to answer the question: What role does Python play in current software development and what are its future prospects? This analysis aims to understand the impact of Python on the software industry and assess how its evolution may influence future technological trends. Methods: To address this objective, a literature review was conducted to gather relevant information about Python. Rigorous selection criteria were established to ensure the quality and timeliness of the consulted sources, and a data analysis was carried out that combined qualitative and quantitative approaches. Results: The article summarizes the main advantages and disadvantages of Python, as well as exploring its various areas of application. Python offers advantages such as ease of learning and a robust ecosystem of libraries, but it also presents disadvantages such as slower execution speed compared to other languages. Conclusions: In conclusion, the study synthesizes the results obtained, evaluates the current use of Python in software development, and provides practical recommendations for developers, highlighting the importance of staying updated with the latest versions and tools available.

DNA Microarray Technology Principles and Applications in Genetic Research

DNA microarray technology, a high-throughput gene analysis tool, has played a crucial role in genetic research. This paper explores the fundamental principles of DNA microarray technology, including its working mechanisms, sample preparation, and types of chips. It emphasizes the applications of DNA microarrays in detecting genetic variations and analyzing gene expression profiles, illustrating examples in single nucleotide polymorphism (SNP) analysis and genome-wide association studies (GWAS). The paper also discusses the technical details of high-throughput gene expression measurement and differential expression analysis. Additionally, it analyzes the main advantages of DNA microarray technology, such as high throughput and sensitivity, while also noting its limitations, including data interpretation complexity and technical costs. Finally, the paper looks forward to future development trends in DNA microarray technology, particularly its potential applications in personalized medicine.

Exploring the Advancements and Applications of Oral Thin Film Technology

This comprehensive review delves into the recent advancements and diverse applications of oral thin film (OTF) technology in the field of pharmaceuticals. The aim is to provide a thorough exploration of the evolution of OTFs, their unique characteristics, and their expanding role in drug delivery systems. A systematic analysis of the literature was conducted to gather information on the formulation techniques, properties, and challenges associated with OTFs. Additionally, recent developments, innovations, and future trends in OTF technology were examined to understand the dynamic landscape of this drug delivery system. The review highlights the key properties of OTFs, including rapid disintegration, enhanced bioavailability, and patient-centric advantages. Various manufacturing techniques, such as solvent casting, hot melt extrusion, and 3D printing, were explored for their impact on OTF formulation. Challenges, including stability issues and taste masking complexities, were identified. Recent innovations, such as nanotechnology integration, personalized medicine applications, and the use of digital health platforms, showcase the ongoing efforts to overcome these challenges. Oral thin film technology stands at the forefront of pharmaceutical innovation, offering a patient-friendly and adaptable drug delivery system. As evidenced by recent developments, the integration of advanced technologies, personalized medicine approaches, and sustainable practices positions OTFs as a transformative force in the future of drug delivery. The exploration of these advancements and applications contributes to a deeper understanding of the potential impact of OTF technology on healthcare.

Insights into the Development Trends of Industrial Large Language Models

In recent years, Large Language Models (LLMs) with massive parameters and complex structures have achieved significant breakthroughs in fields such as natural language processing and image generation, driving their widespread application in industrial sectors. Despite the enormous potential of industrial AI models in areas like design and development, monitoring and management, quality control, and maintenance, their actual construction and deployment still face a lot of challenges, including inherent model deficiencies and difficulties in aligning with industrial requirements. Future technological development trends include the generation of customized industrial datasets, the collaborative optimization of large and small models, the enhancement of adaptive capabilities, and the application of Retrieval-Augmented Generation (RAG) technology. These trends are expected to improve the effectiveness and scalability of AI models, better meeting the needs of the industrial domain. This paper systematically discusses the challenges, technological development trends, and practical applications and deployment of industrial AI models, providing valuable insights for future directions.

Trace the evolution path of pharmaceutical wastewater treatment technology based on a patent perspective

ABSTRACT This paper discusses the research hotspots and future development trends of pharmaceutical wastewater treatment technology, in order to provide valuable reference and guidance to promote the development of technology. First, the search path counting (SPC) algorithm is utilized to identify the global main path to perform a preliminary analysis of the technology evolution path from a macro perspective. Second, according to the life cycle, S-curve divides the time windows of the temporal themes and uses the Latent Dirichlet Allocation (LDA) modeling to identify the themes under each time window. Then, a visualized Sankey diagram is generated to determine the evolutionary relationship, which can be supplemented with the paths of technological evolution from the micro point of view. Finally, six research hotspots of pharmaceutical wastewater treatment technology were found, which are compounding agents, advanced oxidation technology, nanomaterials, artificial intelligence (AI) technology, membrane pollution prevention, and various combinations of wastewater treatment technology. The study also predicted its future development direction.

AI-Powered Predictive Customer Lifetime Value: Maximizing Long-Term Profits

In an era where data-driven decision-making is critical to business success, understanding and optimizing Customer Lifetime Value (CLV) has become a strategic priority for companies across industries. CLV, which estimates the total revenue a business can expect from a customer throughout their relationship, is crucial for identifying high-value customers and tailoring marketing strategies to maximize profitability. However, traditional methods of calculating CLV often rely on historical data and linear models, limiting their accuracy and adaptability in a rapidly changing market environment. The integration of Artificial Intelligence (AI) into predictive analytics has brought about a paradigm shift in how businesses approach CLV. AI-powered predictive models leverage machine learning algorithms to analyze vast amounts of data, uncover complex patterns, and make highly accurate CLV predictions. These models can dynamically adjust to changes in customer behavior, market conditions, and other external factors, providing businesses with a more precise and actionable understanding of their customer base. This article explores the transformative potential of AI in predictive CLV modeling, examining the various techniques and data sources that drive these advanced models. We will discuss the strategic benefits of AI-driven CLV, including personalized marketing, optimized customer segmentation, and enhanced customer retention strategies. Additionally, we will address the challenges associated with implementing AI-powered CLV models, such as data privacy concerns, integration with existing systems, and the interpretation of AI-generated insights. Through a detailed analysis of industry case studies, this article highlights the practical applications of AI-powered CLV models in maximizing long-term profits. We will also explore future trends in AI technology and their potential impact on CLV predictions, offering insights into how businesses can stay ahead of the curve in an increasingly competitive landscape. By the end of this article, readers will have a comprehensive understanding of how AI can revolutionize CLV predictions and drive sustained business growth.

Terahertz Spectroscopy in the Field of Food Safety: A Review

with the continuous improvement of people's living standards, food quality and safety problem has caused the wide attention of the whole society, the traditional food quality detection method has certain limitations, terahertz spectral technology (THZ) is a new spectral detection technology, its strong perspective, efficient spectral resolution ability, special fingerprint and nondestructive, in the field of food quality and safety detection has important application value. Due to the high efficiency of food quality and the need for accurate nondestructive testing, automated nondestructive testing for food quality and safety has aroused great interest from the food sector. Faster, accurate, reliable and simplified techniques are needed to classify good quality. With their unique low-energy, penetrating, rapid and non-destructive techniques are widely used as a non-destructive and cost-effective method in the food sector. This paper summarizes the principles and instruments of terahertz spectrum, and introduces the research progress of terahertz spectral detection in food, analyzes the problems in the field of food quality and safety detection, and discusses the future development trend of terahertz spectral technology.

Designing AR Interfaces for Enhanced User Experience

Augmented Reality (AR) interfaces are transforming biological education and research by providing immersive and interactive learning environments that increase user engagement and learning results. This study analyzes the use of augmented reality (AR) technology in biological sciences, highlighting the importance of User Experience (UX) design concepts in improving AR interfaces for educational effectiveness. The research provides a comprehensive overview of designing AR interfaces tailored to biological education, highlighting intuitive navigation, interactive feedback mechanisms, and personalized learning experiences. By examining current advancements and future trends in AR technology, the paper identifies key opportunities for innovation in educational settings. A poll of sixty students was conducted to collect data on demographics, AR usage experience, educational efficacy, user satisfaction, and perceived advantageous features. The data indicate that AR is well-received, with high scores for simulation realism, ease of use, and engagement. This lecture finishes by bringing together information about augmented reality's transformative potential in biology education and research. It proposes avenues for further research and development to harness the full capabilities of AR technology, shaping the future of learning in the biological sciences.

Drones in Action: A Comprehensive Analysis of Drone-Based Monitoring Technologies

Unmanned aerial vehicles (UAVs), commonly referred to as drones, are extensively employed in various real-time applications, including remote sensing, disaster management and recovery, logistics, military operations, search and rescue, law enforcement, and crowd monitoring and control, owing to their affordability, rapid processing capabilities, and high-resolution imagery. Additionally, drones mitigate risks associated with terrorism, disease spread, temperature fluctuations, crop pests, and criminal activities. Consequently, this paper thoroughly analyzes UAV-based surveillance systems, exploring the opportunities, challenges, techniques, and future trends of drone technology. It covers common image preprocessing methods for drones and highlights notable one- and two-stage deep learning algorithms used for object detection in drone-captured images. The paper also offers a valuable compilation of online datasets containing drone-acquired photographs for researchers. Furthermore, it compares recent UAV-based imaging applications, detailing their purposes, descriptions, findings, and limitations. Lastly, the paper addresses potential future research directions and challenges related to drone usage

Enhancing financial reporting accuracy and compliance efficiency in legal firms through technological innovations

This review paper explores the transformative impact of technological innovations on financial reporting accuracy and compliance efficiency within legal firms. It examines the current challenges legal firms face in maintaining accurate financial records and adhering to regulatory requirements, highlighting issues such as manual errors, complex transactions, and evolving regulations. The paper delves into the roles of automation, artificial intelligence (AI), data analytics, and blockchain technology in addressing these challenges, demonstrating how these tools can enhance financial precision, transparency, and operational efficiency. Additionally, it discusses the future trends in regulatory technology (RegTech), integrated compliance management systems, and real-time monitoring and reporting, emphasizing their potential to streamline compliance processes further. Practical recommendations are provided for legal firms to adopt and integrate these emerging technologies successfully. The paper concludes by underscoring the critical importance of technological innovation in enhancing legal firms' financial and compliance capabilities, ensuring they remain competitive and compliant in a dynamic regulatory environment. Keywords: Financial Reporting, Compliance Efficiency, Legal Firms, Artificial Intelligence, Blockchain Technology, RegTech.

Intelligent Cockpits for Connected Vehicles: Taxonomy, Architecture, Interaction Technologies, and Future Directions.

Highly integrated information sharing among people, vehicles, roads, and cloud systems, along with the rapid development of autonomous driving technologies, has spurred the evolution of automobiles from simple "transportation tools" to interconnected "intelligent systems". The intelligent cockpit is a comprehensive application space for various new technologies in intelligent vehicles, encompassing the domains of driving control, riding comfort, and infotainment. It provides drivers and passengers with safety, comfort, and pleasant driving experiences, serving as the gateway for traditional automobile manufacturing to upgrade towards an intelligent automotive industry ecosystem. This is the optimal convergence point for the intelligence, connectivity, electrification, and sharing of automobiles. Currently, the form, functions, and interaction methods of the intelligent cockpit are gradually changing, transitioning from the traditional "human adapts to the vehicle" viewpoint to the "vehicle adapts to human", and evolving towards a future of natural interactive services where "humans and vehicles mutually adapt". This article reviews the definitions, intelligence levels, functional domains, and technical frameworks of intelligent automotive cockpits. Additionally, combining the core mechanisms of human-machine interactions in intelligent cockpits, this article proposes an intelligent-cockpit human-machine interaction process and summarizes the current state of key technologies in intelligent-cockpit human-machine interactions. Lastly, this article analyzes the current challenges faced in the field of intelligent cockpits and forecasts future trends in intelligent cockpit technologies.

Advances and Challenges in Random Access Techniques for In Vitro DNA Data Storage.

With digital transformation and the general application of new technologies, data storage is facing new challenges with the demand for high-density loading of massive information. In response, DNA storage technology has emerged as a promising research direction. Efficient and reliable data retrieval is critical for DNA storage, and the development of random access technology plays a key role in its practicality and reliability. However, achieving fast and accurate random access functions has proven difficult for existing DNA storage efforts, which limits its practical applications in industry. In this review, we summarize the recent advances in DNA storage technology that enable random access functionality, as well as the challenges that need to be overcome and the current solutions. This review aims to help researchers in the field of DNA storage better understand the importance of the random access step and its impact on the overall development of DNA storage. Furthermore, the remaining challenges and future research trends in random access technology of DNA storage are discussed, with the goal of providing a solid foundation for achieving random access in DNA storage under large-scale data conditions.