Cost-Efficient Continuous Edge Learning for Artificial-Intelligence-of-Things (AIoT)

Artificial Intelligence (AI) mechanisms are more and more frequently applied to all sorts of civil engineering problems. New methods and algorithms which allow civil engineers to use these techniques in a different way on diverse problems are available or being made available. One AI techniques stands out over the rest: Artificial Neural Networks (ANN). Their most remarkable traits are their ability to learn, the possibility of generalization and their tolerance towards mistakes. These characteristics make their use viable and cost-efficient in any field in general, and in Structural Engineering in particular. The most extended construction material nowadays is concrete, mainly because of its high resistance and its adaptability to formwork during its fabrication process. Along this chapter we will find different applications of ANNs to structural concrete.

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An update on novel approaches for diagnosis and treatment of SARS-CoV-2 infection

Cell & Bioscience ◽

10.1186/s13578-021-00674-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Azadeh Safarchi ◽

Shadma Fatima ◽

Zahra Ayati ◽

Fatemeh Vafaee

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Vaccine Development ◽

Health Workers ◽

Diagnosis And Treatment ◽

Therapeutic Approaches ◽

Traditional Medicines ◽

Frontline Health Workers ◽

Novel Approaches ◽

Cost Efficient

AbstractThe ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health and economic crisis worldwide which united global efforts to develop rapid, precise, and cost-efficient diagnostics, vaccines, and therapeutics. Numerous multi-disciplinary studies and techniques have been designed to investigate and develop various approaches to help frontline health workers, policymakers, and populations to overcome the disease. While these techniques have been reviewed within individual disciplines, it is now timely to provide a cross-disciplinary overview of novel diagnostic and therapeutic approaches summarizing complementary efforts across multiple fields of research and technology. Accordingly, we reviewed and summarized various advanced novel approaches used for diagnosis and treatment of COVID-19 to help researchers across diverse disciplines on their prioritization of resources for research and development and to give them better a picture of the latest techniques. These include artificial intelligence, nano-based, CRISPR-based, and mass spectrometry technologies as well as neutralizing factors and traditional medicines. We also reviewed new approaches for vaccine development and developed a dashboard to provide frequent updates on the current and future approved vaccines.

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Crowd-Assisted Disaster Scene Assessment with Human-AI Interactive Attention

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i03.5658 ◽

2020 ◽

Vol 34 (03) ◽

pp. 2717-2724 ◽

Cited By ~ 1

Author(s):

Daniel (Yue) Zhang ◽

Yifeng Huang ◽

Yang Zhang ◽

Dong Wang

Keyword(s):

Artificial Intelligence ◽

Social Media ◽

Disaster Response ◽

State Of The Art ◽

Mobile Sensing ◽

Human Intelligence ◽

Detection Time ◽

Learning Techniques ◽

Salient Regions ◽

Cost Efficient

The recent advances of mobile sensing and artificial intelligence (AI) have brought new revolutions in disaster response applications. One example is disaster scene assessment (DSA) which leverages computer vision techniques to assess the level of damage severity of the disaster events from images provided by eyewitnesses on social media. The assessment results are critical in prioritizing the rescue operations of the response teams. While AI algorithms can significantly reduce the detection time and manual labeling cost in such applications, their performance often falls short of the desired accuracy. Our work is motivated by the emergence of crowdsourcing platforms (e.g., Amazon Mechanic Turk, Waze) that provide unprecedented opportunities for acquiring human intelligence for AI applications. In this paper, we develop an interactive Disaster Scene Assessment (iDSA) scheme that allows AI algorithms to directly interact with humans to identify the salient regions of the disaster images in DSA applications. We also develop new incentive designs and active learning techniques to ensure reliable, timely, and cost-efficient responses from the crowdsourcing platforms. Our evaluation results on real-world case studies during Nepal and Ecuador earthquake events demonstrate that iDSA can significantly outperform state-of-the-art baselines in accurately assessing the damage of disaster scenes.

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Implementation of Artificial Intelligence Wheel Chair for Differently-abled Person

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c4238.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 1052-1054

Keyword(s):

Artificial Intelligence ◽

Artificial Intelligent ◽

Rf Receiver ◽

Rf Transmitter ◽

Wheel Chair ◽

Arduino Uno ◽

Cost Efficient ◽

Mode Of Transport ◽

Physically Challenged

The vehicle is designed by taking into consideration of the physically challenged people especially the paraplegic patients. These people are living in our vicinity with paralyzed legs, their mode of transport from one place to another is through the wheel chairs. The normal wheel chair has to be operated manually with more man power, this eventually makes tiresome for people to cover long distances, in order to overcome such hardships faced by those people artificial intelligent wheel chair is proposed work. The vehicle is being controlled by the analog sensors fitted in the patient’s hand. The device used here is an accelerometer MPU 6050 sensor. The arduino nano board and arduino uno board is acting as an interface between the accelerometer and RF transmitter, DC gear motor and the RF receiver respectively. Coding is developed be the principles of accelerometer in x, y and z directions. The vehicle moves in all four direction according to the gesture of the patient. On the whole the vehicle is patient friendly and cost efficient.

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FinAID, A Financial Advisor Application using AI

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.a2951.059120 ◽

2020 ◽

Vol 9 (1) ◽

pp. 2282-2286

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Global Economy ◽

Efficient Solution ◽

Cost Effective ◽

Financial Advisors ◽

Financial Advisor ◽

Current Scenario ◽

Cost Efficient

The need for skilled financial advisors is more than ever in the current scenario when there are in-numerous moneymaking strategies and at the same time, the global economy might be on the verge of collapse. Also there is a pure lack of good financial advisors and even if you find one, you will end up paying a hefty amount. The current proposed application fulfils the above-stated demand in a cost-effective and reliable way. The proposed system automates the job of a financial advisor using Artificial Intelligence. It provides the user with a simple and easy to use interface where every individual will have their own account handled by Google’s firebase platform. The application uses 'Plaid' API which allows app to send a request to the corresponding bank server and fetch the account details of an individual. Logged in user is shown a very comprehensive representation of their account details which also includes category-wise expenditure, their investment, and the savings. One of the unique parts of this project is a Chatbot which is ever ready to answer the queries of the user related to their accounts and finance. Dialogflow will help in the functionality of Chatbot incorporating Google's machine learning expertise. The proposed application will help provide every needy individual a very reliable, easy to use, and cost-efficient solution to their problem of having a personal financial advisor.

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Use of Artificial Intelligence and Machine Learning in Games

International Journal of Advanced Research in Science, Communication and Technology ◽

10.48175/ijarsct-611 ◽

2020 ◽

pp. 114-118

Author(s):

Nachiket Jadhav ◽

Aniket Matodkar ◽

Anish Mandhare ◽

Sujata Bhairnallykar

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Video Games ◽

The Other ◽

Hardware Support ◽

Learning In Games ◽

Game Play ◽

Cost Efficient

With modern video games surpassing every set of expectations in terms of graphics, game play, mechanics and hardware support, Artificial Intelligence in video games has also come a long way, from when it was first implemented in 1951. Although every set of games has an AI unique to itself, many of the algorithms are now developed such that they can be implemented in various games without any major changes in coding. But this could lead to the players exploiting AI in a single game to break the other games as well. Though this could be easily fixed by changing some minor fragments of algorithms, it would very well be an efficient way of developing complex AI for many games at once. This paper focuses on providing a cost-efficient way to implement AI algorithms that would benefit most of the upcoming and future games that will depend on AI to make themselves more dynamic to the players. This is done by taking the examples of various AI algorithms implemented in games like Pacman, Dota2, Tom Clancy's- The Division and many more.

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An Update on Novel Approaches for Diagnosis and Treatment of SARS-CoV-2 Infection

10.31219/osf.io/xg6z5 ◽

2021 ◽

Author(s):

Azadeh Safarchi ◽

Shadma Fatima ◽

Zahra Ayati ◽

Fatemeh Vafaee

Keyword(s):

Public Health ◽

Artificial Intelligence ◽

Vaccine Development ◽

Health Workers ◽

Diagnosis And Treatment ◽

Therapeutic Approaches ◽

Traditional Medicines ◽

Frontline Health Workers ◽

Novel Approaches ◽

Cost Efficient

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made serious public health and economic crisis worldwide which united global efforts to develop rapid, precise, and cost-efficient diagnostics, vaccines, and therapeutics. Numerous multi-disciplinary studies and techniques have been designed to investigate and develop various approaches to help frontline health workers, policymakers, and populations to overcome the disease. While these techniques have been reviewed within individual disciplines, it is now timely to provide a cross-disciplinary overview of novel diagnostic and therapeutic approaches summarizing complementary efforts across multiple fields of research and technology. Accordingly, we reviewed and summarized various advanced novel approaches used for diagnosis and treatment of COVID-19 to help researchers across diverse disciplines on their prioritization of resources for research and development and to give them a better picture of the latest techniques. These include artificial intelligence, nano-based, CRISPR-based, and mass spectrometry technologies as well as neutralizing factors and traditional medicines. We also reviewed new approaches for vaccine development and developed a dashboard to provide frequent updates on the current and future approved vaccines.

Download Full-text