INTELLIGENT SURVEILLANCE BASED ON NORMALITY ANALYSIS TO DETECT ABNORMAL BEHAVIORS

2009 ◽  
Vol 23 (07) ◽  
pp. 1223-1244 ◽  
Author(s):  
JAVIER ALBUSAC ◽  
DAVID VALLEJO ◽  
LUIS JIMENEZ-LINARES ◽  
J. J. CASTRO-SCHEZ ◽  
LUIS RODRIGUEZ-BENITEZ
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Framework ◽  
Surveillance System ◽  
Semantic Information ◽  
Expert Knowledge ◽  
Outdoor Environment ◽  
Intelligent Surveillance ◽  
Artificial Intelligence Techniques ◽  
Definition Of ◽  
Abnormal Behaviors

Intelligent surveillance refers to using Artificial Intelligence techniques in order to improve surveillance and deal with semantic information obtained from low-level security devices. In this context, the use of expert knowledge may offer a more realistic solution when dealing with the design of a surveillance system. In this work, a conceptual framework based on normality analysis to detect abnormal behaviors by means of normality concepts is presented. A normality concept specifies how a certain object should ideally behave in a concrete environment depending on such a concept. The definition of the normal path concept is studied in depth in order to analyze behaviors in an outdoor environment.

scholarly journals How Companies are Applying AI to the Business Strategy Formulation

2019 ◽  
Vol 5 (8) ◽  
pp. 77
Author(s):  
M S S El Namaki
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Framework ◽  
Business Strategy ◽  
Fundamental Change ◽  
Strategy Formulation ◽  
Strategic Behaviour ◽  
Substantial Progress ◽  
Competitive Behaviour ◽  
Definition Of ◽  
Market Strategies

Computing equipment capable of what one may term partial and quasi-intelligent behaviour, commonly referred to as Artificial Intelligence (AI), is assuming a key role in business. The probability is high that this Artificial Intelligence (AI) will lead to a fundamental change in the process of business strategy formulation as much as the very contents of this strategic behaviour. Product and market strategies and the resultant competitive behaviour will, more likely than not, be the outcome of those artificial intelligence processes and reiterations. A start is made and one can observe substantial progress in this direction. Who has done it and is there a conceptual framework behind this strategic behaviour? This will be the focus of this article The article starts with a brief definition of artificial intelligence and a basic framework of the concept. Seven case studies follow supporting the hypothesis that AI is penetrating the business strategy arena and leading to a fundamental change in the concept as much as the application. Those cases were drawn from different industries, and countries. A conceptual framework is accordingly derived and positioning of those case companies within this conceptual framework is done. The article is based on contemporary frameworks of AI and the cases are drawn from contemporary analysis of strategic behaviour. The conceptual model could provide an instrument for business AI application.

Expert Systems in Distance Education

2018 ◽  
pp. 1410-1423
Author(s):  
Duygu Mutlu-Bayraktar ◽  
Esad Esgin
Keyword(s):  
Artificial Intelligence ◽  
Distance Education ◽  
Natural Language ◽  
Expert Systems ◽  
Expert Knowledge ◽  
Computer Systems ◽  
Educational Environments ◽  
Artificial Environment ◽  
Present Solution ◽  
Definition Of

Computers have been used in educational environments to carry out applications that need expertise, such as compiling, storing, presentation, and evaluation of information. In some teaching environments that need expert knowledge, capturing and imitating the knowledge of the expert in an artificial environment and utilizing computer systems that have the ability to communicate with people using natural language might reduce the need for the expert and provide fast results. Expert systems are a study area of artificial intelligence and can be defined as computer systems that can approach a problem for which an answer is being sought like an expert and present solution recommendations. In this chapter, the definition of expert systems and their characteristics, information about the expert systems in teaching environments, and especially their utilization in distance education are given.

Expert Systems in Distance Education

2015 ◽  
pp. 136-148 ◽  
Author(s):  
Duygu Mutlu-Bayraktar ◽  
Esad Esgin
Keyword(s):  
Artificial Intelligence ◽  
Distance Education ◽  
Natural Language ◽  
Expert Systems ◽  
Expert Knowledge ◽  
Computer Systems ◽  
Educational Environments ◽  
Artificial Environment ◽  
Present Solution ◽  
Definition Of

Computers have been used in educational environments to carry out applications that need expertise, such as compiling, storing, presentation, and evaluation of information. In some teaching environments that need expert knowledge, capturing and imitating the knowledge of the expert in an artificial environment and utilizing computer systems that have the ability to communicate with people using natural language might reduce the need for the expert and provide fast results. Expert systems are a study area of artificial intelligence and can be defined as computer systems that can approach a problem for which an answer is being sought like an expert and present solution recommendations. In this chapter, the definition of expert systems and their characteristics, information about the expert systems in teaching environments, and especially their utilization in distance education are given.

Situational Strategic Awareness Monitoring Surveillance System–Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials

2020 ◽  
Vol 2020 (3) ◽  
pp. 60408-1-60408-10
Author(s):  
Kenly Maldonado ◽  
Steve Simske
Keyword(s):  
Surveillance System ◽  
Cost Effective ◽  
Government Agencies ◽  
Electronic Systems ◽  
Time Data ◽  
Potential Threat ◽  
Intelligent Surveillance ◽  
World Markets ◽  
Programming Software ◽  
And Control

The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.

A Survey on Artificial Intelligence Techniques to Prevent Cyber Crime

2018 ◽  
Vol 8 (5) ◽  
pp. 80
Author(s):  
Juveriya Afreen
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Data Security ◽  
Human Reasoning ◽  
Cyber Crime ◽  
Artificial Intelligence Techniques

Abstract-- With increase in complexity of data, security, it is difficult for the individuals to prevent the offence. Thus, by using any automation or software it’s not possible by only using huge fixed algorithms to overcome this. Thus, we need to look for something which is robust and feasible enough. Hence AI plays an epitome role to defense such violations. In this paper we basically look how human reasoning along with AI can be applied to uplift cyber security.

Support for Study: Online Educational Environments and the Rights to Education

2008 ◽  
Vol 12 (1) ◽  
Author(s):  
Lin Lin ◽  
Karen Swan
Keyword(s):  
Online Learning ◽  
Conceptual Framework ◽  
Collaborative Inquiry ◽  
Expert Knowledge ◽  
The Self ◽  
Open Educational Resource ◽  
Educational Resource ◽  
Online Learners ◽  
Educational Environments ◽  
Independent Inquiry

This paper uses an online learning conceptual framework to examine the “rights to education” that the current online educational environments could provide. The conceptual framework is composed of three inquiries or three spaces for inquiries, namely, independent inquiry, collaborative inquiry, and formative inquiry towards expert knowledge [42] that online learners pursue and undertake in the process of their learning. Our examinations reveal that most online open educational resource environments (OERs) can incorporate more Web2.0 or Web3.0 technologies so as to provide the self-directed learners, who are the main audience of OERs, with more opportunities to participate, collaborate, and co-create knowledge, and accordingly, to achieve their full rights to education.

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