Artificial Intelligence and Robotics

Feasibility studies

- Technical Feasibility study - Environmental - Economic - Organizational - Health

Robotics uses

- Work - Home - Warfare - Online - Underwater exploration

Internet Search engine

A tool used to look for information on the internet

Artificial Intelligence Techniques

Pattern recognition Searching Machine Learning Heuristics

Implementation stage

Developers create the system, following the design documents previously created.

Direct Changeover

Immediate removal of an old system and complete replacement with a new IT system.

Analysis stage

Investigating the current system, determining the organizations requirements for a new system, investigating possible solutions, determining which are feasible, and choosing the most appropriate.

Identification of possible IT solutions

Many projects have possible solutions, ranging from keeping existing systems. Some cases it may be viable to implement a new solution which extends functionality of existing solution

Examples of expert systems

Medical diagnosis Medical image analysis Identifying agricultural pests and diseases Spelling and grammar checking Finance - Decisions on loans Fault diagnosis in various fields

SSADM (structured systems analysis and design method)

Methodology which focuses primarily on the Analysis and Design stages of the SDLC. SSADM has 7 stages

CAPTCHA

Modern form of Turing Test, Completely Automated Public Turing test to tell Humans Apart are designed to prevent spam bots from posting comments or creating false accounts.

Project initiation documents

This a document that bundles up all the information gathered when the project was first initiated.

Computational intelligence

Computational Intelligence usually refers to the ability of a computer to learn specific tasks from data or experimental observation. Computational intelligence focuses on creating systems that 'think' in the same way humans think.

Installation stage

Concerns prepping the organization for the installation of the new system, the hardware and software installation, and the removal of the old system.

Design stage

Covers inputs, process, data structures and outputs required by a system, and relationship between these items.

Purpose of algorithms in expert systems

Finding faults Analysis Product development

Fuzzy logic

Fuzzy logic is the different degrees of truth. Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive.

Inference rules

IF...THEN.. statements which describes rules for a knowledge domain.

Maintenance stage

Maintenance accounts for a large amount of the time and cost associated with IT projects.

Phased changeover

One part of an organisation switches to a new IT system to test it, while others remain using the old system.

Pattern Recognition

Pattern recognition is the automated recognition of patterns and regularities in data. Pattern recognition is closely related to AI and machine learning. It is the process of recognizing patterns by using machine learning algorithms. How it works - The raw data in a pattern recognition application is processed and converted into a form that is amenable for a machine to use. Pattern recognition involves classification and cluster of patterns.

Alpha testing

Performed to verify the software works according to the requirements specification and design documentation.

Project plan

Project manager will be responsible for seeing the project is completed. Project management softwares will be used to monitor the project completion

Prototype

Prototypes of the product may be created at this stage to demonstrate features to the client and check the project is meeting expectation

Parallel running

Running the old system and the new system side by side.

Agile development model

Seeks to address some of the waterfalls models weaknesses and by allowing for greater adaptability.

Expert Systems

an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if-then rules rather than through conventional procedural code

Technical documentation

targeted at system administrators and other developers who may expand or change the system in the future.

Artificial Neural Networks

the attempt to make computers learn in a similar way to humans, by representing neurons in human brains and the electrical impulses which flow between them.

Machine Learning

the extraction of knowledge from data based on algorithms created from training data

Phase out

to gradually stop using something. Gradually stop using a system

Designing softwares

- Data flow diagrams - Entity relationship Diagrams

Problems with Expert systems

- Data may be incorrectly entered, not complete, or out of date. This will have an affect on the reliability and accuracy of the answers by the system - Fault diagnosis system suggesting incorrect solutions may cause inconvenience. - Cannot address problems outside the set domain - Unsuitable for some problems

Project management softwares

- Gantt chart - PERT Chart (Program, Evaluation and review technique)

Methods of Data collection

- Interview - Questionnaires - Observations - literature searches

Disadvantages of Fuzzy logic

- Not accurate as there are different results - Fuzzy systems don't have the capability of machine learning as-well-as neural network type pattern recognition. -

(PMBOK) Project Management Body of Knowledge

A collection of the knowledge and best practices of the project management profession

Feasibility study

A feasibility study is an assessment of the practicality of a proposed project or system.

System Development Life Cycle (SDLC)

The overall process for developing information systems from planning and analysis through implementation and maintenance

Machine Translation

Translating from one human language to another

Quality Assurance

Used to ensure the development team are following standardized practices which is suitable foe the project under development

Expert system components

User interface - Presents input from the user and accepts input from them. Can also present answers and reasoning for answers Knowledge base - Contains data and facts which form the knowledge in specific knowledge domain. Inference engine - Has the job of matching the users input from user interface with the data contained in knowledge base to find appropriate answers

Testing stage

Versions of the software is given to beta testers with the aim of detecting any remaining bugs and testing the software's usability under real world conditions

Waterfall model

Waterfall model flows from analysis to design till maintenance and back to analysis. + Highly structured and allows long term planning + Ensures problems in the analysis stage are found quickly - Lacks adaptability: large IT projects may take such a long time to develop that by the time development stage is reached, requirements identified in analysis stage may have changed.

User Training

Will be carried out before new system can be used under real world conditions.

user documentation

Written or other visual information about an application system, how it works, and how to use it.

Beta testing

a trial of machinery, software, or other products, in the final stages of its development, carried out by a party unconnected with its development

Limitations of AI

Cannot detect human emotions

Define Intelligence

- Ability to respond to the environment - Ability to learn new knowledge - Ability to use logic or reasoning to come to conclusion - Ability to learn from experience - Ability to make evaluations

Advantages of Fuzzy logic

- Allows expert systems to provide multiple answers, with different degrees of certainty. - Similar to human reasoning - High precision - Mostly robust as not many inputs required - Validation and Verification of a fuzzy knowledge-based system needs extensive testing with hardware -

AI advantages and disadvantages

Advantages + Reduction In human error + Takes more risks that Humans cannot take or are afraid to take + Works 24/7 - good for businesses as it can speed up businesses production + Faster decision making compared to humans Disadvantages - Costly to use as AI is updating every day. The hardware and the software need to get updated with time to meet the latest requirements. Makes humans lazy as we depend on AI to come up with inventions and different ideas. We get too addicted to it Artificial Intelligence basically does humans jobs for us which makes us humans useless which leads to unemployment

Project management methodologies

Aim to describe the best approaches for managing those steps, moving between them, or recording successes and failures to enable future improvement

Legacy system

An computer system that is no longer available for purchase or is no longer supported by the manufacturer.

embeded system

An operating system that combines processors and software in a device. - Cell Phones - Computers - GPS - Washing machine

AI capabilities

Capable of making decisions that humans cannot Can do things humans cannot such as calculations Less time consuming Risk-free

Expert system shell

Set of programs used allowing the building of an expert system through the creation if knowledge and rules.

Set Theory

Set theory is when an object either belongs to a set or not. For example, the food is either hot or cold, not both.

7 stages of SSADM

Stage 0 - Feasibility study Stage 1 - Investigation of the current environment Stage 2 - Business system options Stage 3 - Requirement specification Stage 4 - Technical system options Stage 5 - Logical design Stage 6 - Physical design

PRINCE2 (PRojects IN Controlled Environments)

Starts by considering a business case for a project. Planning, organization and risk management are key features of PRINCE2 approach

Turing test

Test by Alan Turing to test whether or not a machine is intelligent.

Natural language processing

The ability of a computer to understand human languages such as English. Can be input such as voice commands or output such as translation of texts

Artificial Intelligence

The development of computer systems that should be able to perform tasks that normally require human intelligence and human knowledge. For example, speech recognition, decision making, or translation between languages.