Adaptive AI in precision agriculture: A review: Investigating the use of self-learning algorithms in optimizing farm operations based on real-time data

Open Access Research Journal of Multidisciplinary Studies, Год журнала: 2024, Номер 7(2), С. 016 - 030

Опубликована: Апрель 7, 2024

This study investigates the transformative impact of adaptive Artificial Intelligence (AI) on precision agriculture, focusing optimizing farm operations through real-time data analysis. The primary objective was to assess how AI technologies enhance efficiency, productivity, and sustainability agricultural practices. Employing a systematic literature review content analysis, methodology involved scrutinizing peer-reviewed articles grey from key databases, applying stringent inclusion exclusion criteria ensure relevance quality. Key findings reveal that significantly improves by enabling precise monitoring management crops, soil, environmental conditions. integration IoT devices machine learning algorithms facilitates leading optimized resource use, reduced impact, increased crop yields. Economic benefits include cost savings efficient management, while advantages encompass minimized chemical use enhanced sustainability. Challenges identified high implementation costs, technical complexity, privacy concerns. However, solutions such as policy support, technological advancements, stakeholder collaboration are proposed overcome these barriers. Lastly, holds potential revolutionize agriculture making it more efficient, sustainable, productive. Future research should focus developing accessible, robust fostering an environment conducive adoption. underscores need for continued innovation support fully realize in agriculture.

Язык: Английский

---

A Secure Blockchain-Enabled Remote Healthcare Monitoring System for Home Isolation

Journal of Sensor and Actuator Networks, Год журнала: 2024, Номер 13(1), С. 13 - 13

Опубликована: Фев. 5, 2024

This article presents a secure framework for remote healthcare monitoring in the context of home isolation, thereby addressing concerns related to untrustworthy client connections hospital information system (HIS) within network. Our proposed solution leverages public blockchain network as distributed database buffer and transmit patient vital signs. The integrates an algorithm gathering transmission signs Ethereum Additionally, we introduce publish/subscribe paradigm, thus enhancing security using TLS channel connect An analysis maintenance cost underscores cost-effectiveness our approach. In conclusion, provides highly economical isolation scenarios.

Язык: Английский

---

A Hybrid-Transformer-Based Cyber-Attack Detection in IoT Networks

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2024, Номер 18(14), С. 90 - 102

Опубликована: Авг. 2, 2024

The concept of the Internet Things (IoT) is significant in today’s world and opens up new opportunities for several organizations. IoT solutions are proliferating fields such as self-driving cars, smart homes, transportation, healthcare, services constantly being created. Over previous decade, society has seen a expansion connectivity. In reality, connectivity will expand variety domains over next few years. Various problems must be overcome to permit effective secure operations. However, growing connections increase potential cyber-attacks since attackers can exploit broad network linked devices. Artificial intelligence (AI) detects prevents cyber assaults by developing adjusting threats weaknesses. this study, we offer novel cyber-detection model networks based on convolutional neural (CNN) transformers. study aims enhance system’s ability identify detect cyberattacks, sophisticated assaults, its performance. experimental findings, using cybersecurity CICIoT2023 dataset, show that CNN-Transformer hazards with an overall accuracy 99.49%. identifying hazardous activity, MLP 99.39%, while XGBoost-pipeline 99.40%.

Язык: Английский

---

A Novel Cloud-Enabled Cyber Threat Hunting Platform for Evaluating the Cyber Risks Associated with Smart Health Ecosystems

Applied Sciences, Год журнала: 2024, Номер 14(20), С. 9567 - 9567

Опубликована: Окт. 20, 2024

The fast proliferation of Internet Things (IoT) devices has dramatically altered healthcare, increasing the efficiency and efficacy smart health ecosystems. However, this expansion created substantial security risks, as cybercriminals increasingly target IoT in order to exploit their weaknesses relay critical information. rising threat landscape poses serious concerns across various domains within where protection patient information integrity medical are paramount. Smart systems, while offering numerous benefits, particularly vulnerable cyber-attacks due integration vast amounts data they generate. Healthcare providers, although unable control actions cyber adversaries, can take proactive steps secure systems by adopting robust cybersecurity measures, such strong user authentication, regular system updates, implementation advanced technologies. This research introduces a groundbreaking approach addressing challenges ecosystems through deployment novel cloud-enabled threat-hunting platform. platform leverages deception technology, which involves creating decoys, traps, false divert away from legitimate systems. By using innovative approach, assesses risks associated with actionable recommendations healthcare stakeholders on how minimize enhance posture IoT-enabled solutions. Overall, pioneering represents significant advancement safeguarding interconnected world ecosystems, providing promising strategy for defending against escalating threats faced industry.

Язык: Английский

---

Proactive ransomware prevention in pervasive IoMT via hybrid machine learning

Indonesian Journal of Electrical Engineering and Computer Science, Год журнала: 2024, Номер 34(2), С. 970 - 970

Опубликована: Март 23, 2024

Advancements in information and communications technology (ICT) have fundamentally transformed computing, notably through the internet of things (IoT) its healthcare-focused branch, medical (IoMT). These technologies, while enhancing daily life, face significant security risks, including ransomware. To counter this, authors present a scalable, hybrid machine learning framework that effectively identifies IoMT ransomware attacks, conserving limited resources devices. assess effectiveness their proposed solution, undertook an experiment using state-of-the-art dataset. Their demonstrated superiority over conventional detection methods, achieving impressive 87% accuracy rate. Building on this foundation, integrates multi-faceted feature extraction process discerns between benign malign actions, with subsequent in-depth analysis via neural network. This advanced is pivotal precisely detecting terminating threats, offering robust solution to secure ecosystem.

Язык: Английский

---

Developing a Decentralized Blockchain Framework with Hyperledger and NFTs for Secure and Transparent Patient Health Records

Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 478 - 489

Опубликована: Янв. 1, 2024

Язык: Английский

---

Data Security Design in Computer Application Software Development from the Perspective of Information Security Environment

Опубликована: Янв. 1, 2024

Information security plays a vital role in computer application software development. With the advent of digital age, large amount sensitive information is stored and transmitted. Ensuring this data critical for individuals organizations alike. So paper studies t

Язык: Английский

---

Securing Medical Data Exchange: A Decentralized Approach Based on the e-IPGPChain Framework

International Journal of Safety and Security Engineering, Год журнала: 2024, Номер 14(3), С. 815 - 829

Опубликована: Июнь 24, 2024

Delivering healthcare services closer to the end user faces a significant challenge in light of frequent cyberattacks that target personal data for disruption, financial gain, and damage purposes.Existing e-health monitoring solutions exhibit limitations related performance, stability, overall system security, which negatively impact medical service delivery reveal technical difficulties privacy availability.This paper introduces novel approach integrates various technologies intending fully decentralize sharing with minimum risks while maintaining high-performance services.Our Solution e-IPGPChain, Leverages Hyperledger Fabric network-related RBAC policies, IPFS, edge computing build robust hybrid storage solution, ensuring optimal availability.Furthermore, proposed solution improves workflow security by employing cryptographic ecosystem tool, GPG (GNU Privacy Guard), an open-source implementation PGP (Pretty Good Privacy), featuring strong lightweight digital signature mechanism named edDSA besides, encryption technology, enhance authenticity, integrity, non-repudiation exchanged among different entities.The performance evaluation focuses on most valuable metrics field such as latency, scalability, processing, availability, indicates result.On other hand, using STRIDE framework identifies key points ensure conformity from angles our against common cyberattacks.Evaluating attacks demonstrates level provided secure workflow.

Язык: Английский

---

The Ethics of AI in Medical Research: A Call for Open and Honest Discussion

Liaquat Medical Research Journal, Год журнала: 2024, Номер 6(2)

Опубликована: Июнь 30, 2024

Artificial intelligence (AI) in healthcare is gaining rapid popularity terms of its application and research. A significant reason for success due to the advances it has made ease use incorporates. Because implications, issues, benefits ease, AI been debated researched extensively. This study examined ethical dilemmas associated with artificial medical The research uses a qualitative method based on content analysis. Authentic Internet resources were used collect secondary data. Once fully integrated into healthcare, several will likely arise, including patient privacy, data security, algorithmically biased results, transparency, human error. Minimizing continuous monitoring possible, but they cannot be eliminated. It possible advancement technology enables imitate cognitive processes humans, which may enhance reliability can also lead negative consequences. As result, new technological developments must applied ethically. An open honest discussion essential awareness understanding ethics, honoring rights, maintaining public trust.

Язык: Английский

---

Applying Optimized Algorithms and Technology for Interconnecting Big Data Resources in Government Institutions

International Journal of Online and Biomedical Engineering (iJOE), Год журнала: 2023, Номер 19(08), С. 4 - 18

Опубликована: Июнь 27, 2023

The quality of the data in core electronic registers has constantly decreased as a result numerous errors that were made and inconsistencies these databases due to growing number created with intention providing services for public administration lack harmonization or interoperability between databases.Evaluating improving by matching linking records from multiple sources becomes exceedingly difficult incredibly large volume different architectures no unique field create interconnection among them.Different algorithms are developed treat issues our focus will be on handle amounts data, such Levenshtein distance (LV) algorithm Damerau-Levenshtein (DL) algorithm.In order analyze evaluate effectiveness using mentioned making improvements algorithms, through this paper we conduct experiments sets more than 1 million records.

Язык: Английский

---