Conversation to Automation in Banking Through Chatbot Using Artificial Machine Intelligence Language

Suhel, Sasha Fathima; Shukla, Vinod Kumar; Vyas, Sonali; Mishra, Ved Prakash

doi:10.1109/icrito48877.2020.9197825

Cited by 77 publications

(31 citation statements)

References 1 publication

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“…IoT has a big influence on lowering healthcare expenses and increasing treatment results. The Internet of things (IoT) is clearly transforming the healthcare industry by redefining the role of gadgets and human touch in medical solution delivery [ 2 , 3 ]. IoMT of wide range is useful in patient conditioning, monitoring, screening, personalized medicine, integrating healthcare professionals, doctors, and hospital networks to patients for remote telemedicines, and patient monitoring.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning in Healthcare System for Quality of Service

Bordoloi

Singh

Sanober

et al. 2022

Journal of Healthcare Engineering

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Deep learning (DL) and machine learning (ML) have a pivotal role in logistic supply chain management and smart manufacturing with proven records. The ability to handle large complex data with minimal human intervention made DL and ML a success in the healthcare systems. In the present healthcare system, the implementation of ML and DL is extensive to achieve a higher quality of service and quality of health to patients, doctors, and healthcare professionals. ML and DL were found to be effective in disease diagnosis, acute disease detection, image analysis, drug discovery, drug delivery, and smart health monitoring. This work presents a state-of-the-art review on the recent advancements in ML and DL and their implementation in the healthcare systems for achieving multi-objective goals. A total of 10 papers have been thoroughly reviewed that presented novel works of ML and DL integration in the healthcare system for achieving various targets. This will help to create reference data that can be useful for future implementation of ML and DL in other sectors of healthcare system.

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Section: Introductionmentioning

confidence: 99%

Deep Learning in Healthcare System for Quality of Service

Bordoloi

Singh

Sanober

et al. 2022

Journal of Healthcare Engineering

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“…rough the application of artificial intelligence (AI) and machine learning (ML), growers can access increasingly sophisticated data and analytics tools, which enables better decisions, improved efficiencies, and reduced waste in food and biofuel production, all while minimizing negative environmental consequences. Subsequently, health-related issues will also decrease [26][27][28][29][30]. As a result, agricultural productivity is often assessed as the market value of the finished product.…”

Section: Introductionmentioning

confidence: 99%

Implementing Machine Learning for Supply-Demand Shifts and Price Impacts in Farmer Market for Tool and Equipment Sharing

Rakhra

Bhargava

et al. 2022

Journal of Food Quality

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Several industries have recently seen the replacement of human labor by automated machinery and equipment. Across the globe, farmers’ attitudes on the use of technology in agriculture are divergent. However, although some people are excited and ready to embrace technology, others are cautious and wary of trying new technologies for the first time. The third category is particularly prevalent in underdeveloped nations such as India, owing to a lack of competence, a lack of effective translation, and most crucially, a lack of financial resources. It is fruitless for the government to attempt to resolve these difficulties due to the fact that they do not take into consideration the changing circumstances and input needs of each agricultural group. Smart Tillage is a cutting-edge framework that was developed to solve the challenges listed above. In India, a decision-based smart engine for the rental and sharing of tools and equipment has been developed, which leverages machine learning methods to proceed towards a selection of tools and equipment. The option is entirely reliant on a variety of input variables, including crop kind, harvest time/month, crop equipment needed, harvest type, and the amount of money available for rental. Additionally, an ideal recommendation engine driven by content and collaborative-based filtering will provide the farmer’s requirements depending on their requirements. In terms of escalation, the proposals would be cost-effective and excellent since they would need little changes in training, technique improvements, and resource management via a new rent-share model similar to that used by Uber. In this work, demand and supply algorithms are used to define market equilibrium, and the results are shown in graphs. This includes discussion of a variety of demand and supply parameters, their impact on market equilibrium prices and quantities, and their effect on shifting demand and supply curves. The many sorts of elasticities (demand, cross-price, supply, income, and so on) are examined, as well as the ramifications for pricing systems that may result from these elasticities.

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“…A web application is platform neutral since all it needs is a web browser. The cross-platform language makes an application look native to the platform or operating system of the client [13,14]. In this process, the choice of the platform mode of the computer room management system is the main problem that the system designers meet.…”

Section: System Platform Modementioning

confidence: 99%

Optimal Design of Intelligent Control System in the Communication Room Based on Artificial Intelligence

Yao

Kler

Khan

et al. 2022

Wireless Communications and Mobile Computing

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With the current data-driven era, there is the potential to employ controllers that can store a large amount of data, which is not achievable with traditional controllers. Our goal is to propose an intelligent controller system for computer room management based on artificial intelligence that maintains data integrity, saves memory, minimizes computation, and simplifies program design. To upgrade the computer room management system’s intelligence that is not high, the management mode that is not flexible, and the distributed large-scale management of the whole school that is difficult to realize, the original system is improved to the distributed computer room management system based on artificial intelligence. By starting from the actual situation of higher vocational college computer room, combined with the characteristics of the school computer room, we designed framework model based on distributed artificial intelligence machine room management system, the system by means of network communication technology and database access technology, put forward the B/S combined with C/S structure to realize the computer room management system model, and used radio frequency identification technology to develop radio frequency card. The results show that the optimization results of the traditional computer automatic control system in the computer room vary greatly and fluctuate between 0.6 and 0.8, while the control results of the automatic control system in this paper keep stable at 0.8, which can reach the ideal state in a short time. Through the outcome, it can be said that the proposed control method can be used of higher level of automation, flexibility, and robustness which will work effectively. Therefore, the improved system integrates software, hardware, communication, and distributed system technology into one, which greatly improves the control effect of computer automatic control process, and control result of computer automatic control process is more stable and has a certain practical application value.

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Conversation to Automation in Banking Through Chatbot Using Artificial Machine Intelligence Language

Cited by 77 publications

References 1 publication

Deep Learning in Healthcare System for Quality of Service

Deep Learning in Healthcare System for Quality of Service

Implementing Machine Learning for Supply-Demand Shifts and Price Impacts in Farmer Market for Tool and Equipment Sharing

Optimal Design of Intelligent Control System in the Communication Room Based on Artificial Intelligence

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