Agriculture Solutions Using Artificial Intelligence

Sahu, Ajay

doi:10.22214/ijraset.2023.54379

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…AI and ML use employee performance data to identify patterns and predict future performance. The insights provided by AI and ML help optimize employee development programs and team performance (Sahu & Sahu, 2019). AI and ML algorithms can be used to make predictions about employee performance, such as identifying which employees are likely to leave the company or predicting which employees are most likely to perform well in certain roles.…”

Section: Artificial Intelligence and Machine Learningmentioning

confidence: 99%

Technology impact: A study on the performance appraisal process in the IT industry

Mohan,

Vasumathi

2024

Multidiscip. Rev.

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This study investigates the impact of technology on the performance appraisal process within the IT industry. Rapid advancements in technology have transformed traditional performance appraisal methods, and understanding the implications of these changes is crucial for organizations striving to optimize their performance management strategies. The use of technology for performance appraisals in the IT industry can introduce several problems that can negatively impact the evaluation process and employee morale. Automated systems may rely on irrelevant or incomplete metrics that do not capture important qualitative aspects of performance. These systems may be prone to errors, biases, and inaccuracies in data collection and interpretation. The findings of this study reveal the significant impact of technology on the performance appraisal process in the IT industry. There are potential solutions for mitigating performance appraisal problems in the IT industry. To ensure that performance appraisal systems are relevant and accurate, organizations can involve employees in the development of metrics and provide regular feedback. The integration of digital tools has enhanced the efficiency and accuracy of data collection, tracking, and analysis, leading to streamlined processes, reduced administrative burdens, and increased data reliability. Real-time communication channels have facilitated more frequent and timely feedback, fostering employee engagement and development.

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Section: Artificial Intelligence and Machine Learningmentioning

confidence: 99%

Technology impact: A study on the performance appraisal process in the IT industry

Mohan,

Vasumathi

2024

Multidiscip. Rev.

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“…The utilization of AI in biology learning share similarities with the use of AI in education in general, the difference is only in the field of study is specific focus on biology learning. Owan et al, (2023) Learning evaluation and assessment Learning aids (Sahu, 2015) Based on its application, various types of AI services can be grouped into six categories, namely teaching assistance (i.e ITS, virtual assistants, personalized learning), learning evaluation (i.e automated grading, AES, CBT), teaching media (i.e VR and AR), virtual classroom (i.e LMS), VOLUME 8 ISSUE 2 JANUARY 2024…”

Section: Artificial Intelligence In Biology Educationmentioning

confidence: 99%

Artificial intelligence in biology and learning biology: A literature review

Aripin,

Gaffar,

Jabar

et al. 2024

mangiferaedu

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Artificial Intelligence (AI) had been developed in various fields of human life. The use of AI brought the world towards a digital transformation that had not been imagined before. One form of AI development in the fields of biology and biology education brought the development of science in both fields far beyond expectations. The use of AI in the fields of biology and biology education had utilized many new methods and discoveries that are beneficial to humans. The purpose of this study was to determine the application of AI in biology and biology learning. The literature review method was used to analyze and synthesize research results from a new perspective. The results of the analysis of various pieces of our literature found various uses of AI. In the field of biology, including AI in the field of biology used for biological data analysis, genetic data analysis, investigation of complex biological phenomena (synthetic biology and system biology), bioinformatics, disease detection, and diagnosis. AI had been utilized in various fields of biological sciences such as medical, agriculture, animal husbandry, and industry for product development and automation in the production process utilizing IoT. There were 24 types of AI utilization in education, especially biology learning, which can be grouped into six groups: personalized and tutoring learning (teaching assistance/tutor), evaluation and assessment, teaching media, enriching learning, virtual classes, and learning aids.

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Agriculture Solutions Using Artificial Intelligence

Cited by 2 publications

References 11 publications

Technology impact: A study on the performance appraisal process in the IT industry

Technology impact: A study on the performance appraisal process in the IT industry

Artificial intelligence in biology and learning biology: A literature review

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