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AI is the science of making machines do things that would require intelligence if done by men. It includes reasoning, learning, planning, speech recognition, vision, and language understanding. These machines are being used today in a wide variety of applications, such as monitoring credit card fraud, making autonomous decisions on space missions, watching for attacks from computer network hackers, diagnosing faults in aircraft, enabling human–machine speech interfaces, and making the characters in a video game behave in a more human-like way.

The main unifying theme is the idea of an intelligent agent. We define the AI as the study of agents that receive percepts from the environment and perform actions. Each such agent implements a function that maps percepts sequences to actions, and we cover different ways to represent these functions, such as real-time conditional planners, neural networks, and decision theoretic systems. We treat robotics and vision as occurring in the service of achieving goals.

Eliza, the program was able to converse about any subject, because it stored subject information in data banks.

Keywords: Turing test – Intelligent agents - Neural Networks – Genetic Programming – Planning – Fuzzy Logic – Robotics – Pattern recognition - Natural language processing – Deep blue - Eliza - video clip.

Index:

Introduction

Turing test

Classification

Intelligent agents

What belongs to AI?

Applications

Chess and AI

Computer Vs. Human Brain

Fuzzy-Logic and AI

Eliza

Conclusion (AI present & future)

References

1. Introduction

After WWII, a number of people independently started to work on intelligent machines. The English mathematician Alan Turing gave a lecture on it in 1947. I would compare attempts to create AI with man’s historical attempts at flight.

2. Turing test (Article of Computational Intelligence: 1950)

He argued that if the machine could successfully pretend to be human to a knowledgeable observer then you certainly should consider it intelligent. The observer could interact with the machine and a human by teletype (to avoid requiring that the machine imitate the appearance or voice of the person), and the human would try to persuade the observer that it was human and the machine would try to fool the observer.

3. Classification

This is a discipline with two strands: science and engineering. The scientific strand attempts to understand the requirements for, and mechanisms enabling, intelligence of various kinds in humans, other animals and information processing machines and robots. The engineering strand attempts to apply such knowledge in designing useful new kinds of machines and helping us to deal more effectively with natural intelligence, e.g. in education and therapy.

Bottom-up theorists believe the best way to achieve artificial intelligence is to build electronic replicas of the human brain’s complex network of neurons, while the top-down approach attempts to mimic the brain’s behavior with computer programs. Moreover there is a lot of difference between the AI simulated system and a program with the large database. This is discussed later on under the topic of chess-AI.

4. Intelligent Agents

An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators. An agent’s percept sequence is the complete history of everything the agent has ever perceived.

A rational agent is one that does the right thing. A Performance measures embodies the criterion of a success of an agent’s behavior. When an agent is plunked down in an environment, it generates a sequence of actions according to the percepts it receives.

The Nature Of Environments

Specifying environment (PEAS – Performance, Environment, Actuators, Sensors) under the heading of the task environment we group the performance measure, the environment, and the agent’s actuators and sensors.

E.g., an automated taxi driver.

Agent Type Performance

Measure Environment Actuators Sensors

Taxi driver Safe, fast, legal, comfortable trip, maximize profits Roads, other traffic, pedestrians, customers Steering, accelerator, brake, signal, horn, display Cameras, sonar, speedometer, GPS, odometer, accelerometer, engine sensors, keyboard

It is better to design performance measures according to what one wants in the environment, rather than according to how one think the agent should behave

More specifically, the learning ability needs to be autonomous, goal-directed, and highly adaptive:

Autonomous — Learning occurs both automatically, through exposure to sense data (unsupervised), and through bi-directional interaction with the environment, including exploration/ experimentation (self-supervised).

Goal-directed – Learning is directed (autonomously) towards achieving varying and novel goals and sub-goals — be they ‘hard-wired’, externally specified, or self-generated. Goal-directedness also implies very selective learning and data acquisition (from a massively data-rich, noisy, complex environment).

Adaptive – Learning is cumulative, integrative, and contextual and adjusts to changing goals and environments. General adaptivity not only copes with gradual changes, but also seeds and facilitates the acquisition of totally novel abilities.

5. What Belongs to Artificial Intelligence

Neural Networks

Artificial Neural Networks, often just called Neural Networks (NN), are modelled on the human brain. The internal structure of the network, composed of a small number of artificial neurons, implies that the information learnt is not perfect. Artificial Neural Networks have been used successfully in visual pattern recognition, even human faces and complex industrial components can be differentiated. Artificial Neural Networks have been used in speech recognition system to decipher audible language.The technique used is that of a highly parallel network of simple processing elements. Each element has some similarity with animal nerve or brain cells called neurons

Genetic Programming

Genetic programming is an excellent way of evolving algorithms that will map data to a given result when no set formula is known. Mathematicians/programmers could normally find algorithms to deal with a problem with 5 or so variables, but when the problem increases to 10, 20, 50 variables the problem becomes close to impossible to solve. Briefly, how a GP-powered program works is that a series of randomly generated expression trees are generated that represent various formulas. These trees are then tested against the data, poor ones discarded, good ones kept and breed. Mutation, crossover, and all of the elements in genetic algorithms are used to breed the ‘highest-fitness’ tree for the given problem. At best, this will perfectly match the variables to the answer, other times it will generate an answer very close to the wanted answer.

Planning, problem solving, automatic design:

Planning involves finding a sequence of actions that can lead from the current state, to the goal state. Given a complex problem and a collection of resources, constraints and evaluation criteria create a solution which meets the constraints and does well or is optimal according to the criteria, or if that cannot be done propose some good alternatives.

Machine Learning

Machine learning is becoming increasingly popular, and equally important. People realise that it is theoretically much easier to get a machine to learn something from facts, rather than have to spend time teaching it explicitly. The quality of the learning algorithm is of course a major factor!

Constraint Satisfaction

Here, the problem is modeled as a set of variables, which can be assigned particular values. Different types of constraints are set-up on these variables (equality, numerical constraints), in order to specify the requirements for the problem. A search is then performed on the variables, in order to find the potential solutions. There are many nifty tricks involved to partly resolve constraints in order to guide the search more efficiently (this is called a heuristic search). The problems solved can also be a combinatorial optimisation, where a particular solution has a better value than another, and the best needs to be found. The class of problems usually solved is NP-complete, where the complexity increases exponentially as the problem size increases linearly.

Search and Optimization

There are many kinds of searches, the simplest of which involve trying out all the solutions in a particular order. The entire set of possible solutions is called the search space.

Decision Tree Learning

A decision tree is a structure that allows learning of opinions (e.g. good or bad) about objects based on their attributes (length, colour…). Given a series of examples, the learning algorithm can build a decision tree that will be able of classifying new examples. If the new examples are handled correctly, nothing is done. Otherwise, the structure of the tree is modified until the correct results are displayed. The challenge is getting the algorithm to perform well on very large sets of data, handling errors in values (noise), and determining the optimal fit of the tree to the training and test data.

Data Mining

This is the process of extracting useful rules from very large sets of data. Data Mining is a term used to describe the process whereby software tools examine a company data base in order to locate information which may have complex parameter connectivity. Such information would normally be inaccessible to the human expert due to the enormous quantity of data and combinatorial tests which would have to be performed. A simple example may be a data base of company products and parameters which describe their applicability to various sectors of the market.

Bayesian Networks

Bayesian Networks models the relationship between variables. This is called conditional dependence: a state of a variable may depend on many others. This can be represented as a graph, and there’s a clever algorithm to estimate the probability of unknown events given existing knowledge. Admittedly, one common complaint against this approach relates to the design; it can be very tedious to model such networks. As such, learning the structure and the inference between variables seems like an appealing option.

Artificial Life

Artificial Life (A-Life) is the study of artificial or computer based systems, which exhibit life like behavior. Computer simulations of individual agents or populations of agents can be used to investigate many of the properties of living systems. In some cases, mechanically constructed agents are provided with basic functionality and allowed to interact with real environments. This is a very popular aspect of Artificial Intelligence, which involves modeling and mimicking living systems. This includes anthills, wasp nests, larger forests, towns and cities. To date, very complex and interesting systems have been created by a multitude of very simple entities. For example many ants programmed by very small programs would potentially create an entire system with signs of emergent intelligence.

6. Applications

Robotics

The main aspect of robotics today is mobility. This can be done by learning the task in a virtual simulation, and then applying it to the real robot. If specific conditions of training are respected, the problem has a high probability of working in real life, but this is no guarantee. In practice when moving robotic arms, the arm has a few movement possibilities: the shoulder allows rotations according to two axes, and the elbow also allows two basic rotations. Each of these possibilities is called one degree of freedom. Usually, one controller is assigned to provide movement for one DOF. The task at hand is to learn the optimal combination of controllers, where they can successfully cooperate to perform a given task.

Pattern Recognition

Pattern recognition involves determining the characteristics in specific samples and sorting them into classes; a process called classification. This is usually done with Machine Learning techniques, allowing the system to adapt to the data given to it. It can be applied to detecting single words in speech, recognizing voices, sorting scanned objects by type and filtering out unwanted pictures (among many others). In practice, a way of doing this is to represent the sample as a set of features (e.g. for a sound: pitch, volume, timbre, smoothness). A training set is then created: i.e. a set of samples where the result is known (e.g. for facial recognition: Fred has green eyes and brown hair, Henry has blue eyes and blond hair). The learning mechanism can then learn to associate the features with the known types of sound or image. Depending on the representation, more or less samples are required. With symbolic representations, small numbers of examples are usually required, whereas for fuzzy learning (in neural networks for example) larger training sets are needed.

Natural language processing

It includes production and interpretation of spoken and written language, whether hand-written, printed, or electronic throughout (e.g. email). One of the first approaches was symbolic, assigning semantic meaning to each word (verb, noun, adjective). The basic structure of valid sentences would have to be defined manually, and a search would be performed to match the template with the current sentence. A lot of time needed to be spent resolving ambiguous sentences, and getting the person and tenses of the verbs to match. If the programmer spends enough time creating the sentence templates, the results would be fairly encouraging. But this monotonous task needs to be repeated for new sentence constructs and new languages all together.

A very recent approach is to use statistical analysis of the text. In essence, large parts of books are processed and learning algorithms attempt to extract the rules and patterns. This requires a smarter approach, taking more time to design, but it results in a more flexible program.

Frames

On method that many programs use to represent knowledge are frames. Pioneered by Marvin Minsky, frame theory revolves around packets of information. For example, say the situation was a birthday party. A computer could call on its birthday frame, and use the information contained in the frame, to apply to the situation. The computer knows that there is usually cake and presents because of the information contained in the knowledge frame. Frames can also overlap, or contain sub-frames. The use of frames also allows the computer to add knowledge. Although not embraced by all AI developers, frames have been used in comprehension programs such as Sam.

AI in medicine, including interpretation of medical images, diagnosis, expert systems to aid GPs, monitoring and control in intensive care units, design of prosthetics, design of drugs, intelligent tutoring systems for various aspects of medicine.

AI in many aspects of engineering: fault diagnosis, intelligent control systems, intelligent manufacturing systems, intelligent design aids, integrated systems for sales, design, production, maintenance, expert configuration tools (e.g. ensuring sales staff don’t sell system that won’t work). AI in software engineering includes work on program synthesis, verification, debugging, testing and monitoring of software.

AI in education: including various kinds of intelligent tutoring systems and student management systems. Particular applications might include diagnosis of a student’s knowledge gaps, various kinds of drill and practice tutors, automatic marking of programming assignments and essays, etc.

AI in entertainment: increasingly AI is being used in computer games and in systems for generating and controlling synthetic characters either for textual interaction or generating films with cartoon characters or interactive avatars in virtual worlds.

AI in biology: there are many hard problems in biology where more or less intelligent computer-based systems are being developed, e.g. analysis of DNA, prediction of folded structure of complex molecules, prediction, modeling many biological processes, evolution, development of embryos, behaviors of various organisms.

Architecture, urban design, traffic management: tools to help solve design problems involving multiple constraints, helping to predict the behaviors of people in new environments, tools to analyze patterns in observed phenomena.

Literature, art and music: identification of authors, modeling of processes of generation and appreciation, teaching applications.

Crime prevention and detection: e.g. detection of forgeries, learning to detect evidence of crooked police officers, software to monitor internet transactions, helping to plan police operations, searching police databases for evidence that crimes are committed by the same person, etc.

Space: control of space vehicles and autonomous robots too far from earth to be directly manipulated by humans on earth, because of transmission delays.

Military activities: Various paradigms in AI have been successfully applied in the military field. For example, using an EA (evolutionary algorithm) to evolve algorithms to detect targets given radar/FLIR data, or neural networks differentiating between mines and rocks given sonar data in a submarine.

7. Chess and AI

Deep Blue does not use AI. Then how is AI – deep blue related?

AI-based game playing programs combine intelligence with entertainment. World-champion chess playing programs can see ahead twenty plus moves in advance for each move they make. In addition, the programs have an ability to get progressably better over time because of the ability to learn. Chess programs do not play chess as humans do. In three minutes, Deep Thought (a master program) considers 126 million moves, while human chessmaster on average considers less than 2 moves. The next move comes from exhaustive searches into all moves, and the consequences of the moves based on prior learning. Chess programs, running on Cray super computers have attained a rating of 2600 (senior master), in the range of Gary Kasparov, the Russian world champion.

DEEP BLUE: First of all, this year Deep Blue will be running on a faster system - the latest version of the SP -, which uses 30 P2SC or Power Two Super Chip processors. Last year, Deep Blue averaged about 100 million chess positions per second. This year Deep Blue will work about twice as quickly - that is, 200 million chess positions per second. Incidentally, Garry Kasparov can evaluate approximately three positions per second.

8. Fuzzy Logic and AI

It is often said that computers are too logical and that they can only deal in true or false, yes or no etc. However, Fuzzy Logic allows a computer to deal in everyday human language and actually process terms such as probably, unlikely, quite near etc. Such terms can take their place in computations, allowing the computer to arrive at verifiable results from fuzzy inputs. Another type of fuzzy information is stored in the famous Neural Networks. This is known as a neuro-fuzziness. The information inside an artificial neural network is usually imprecise, due to the weighted connection between neurons (called synapses).

Fuzzy representations have increased in popularity, due to the increased capabilities of computers: more processing power is usually required to create such rules, and interpreting them generally also requires a bit more time. The preferred languages for this type of representation are usually procedural like C, C++ or Pascal.

9. Brain Vs. Computer

A collection of simple cells can lead to thought, action, and consciousness or, in other words, that brains cause minds. Even thought a computer is a million times faster in raw switching speed, the brain ends up being 100,000 times faster at what it does.

Computer Human brain

Computational units 1 CPU, 108 gates 1011 neurons

Storage units 1010 BITS RAM 1011 neurons

1011 bits disk 1014 synapses

Cycle time 10-9 sec 10-3 sec

Bandwidth 1010 bits/sec 1014 bits/sec

Memory updates/sec 109 1014

10. ELIZA

Eliza, Joseph Wiezbaum’s result of trying to make a program converse in English amazed people when it appeared in mid 1960’s. The program was able to converse about any subject, because it stored subject information in data banks. Another feature of Eliza was its ability it picked up speech patterns

Conclusions:

Finally, we come up with many conclusions with regards to future and present of Artificial Intelligence. AI is fascinating, and intelligent computers are clearly more useful than unintelligent computers, so why worry? AI has made possible new applications such as speech recognition systems, inventory control systems, surveillance systems, robots and search engines.

Finally, it seems likely that a large-scale success in AI—the creation of human-level intelligence and beyond—would change the lives of majority of the humankind. The very nature of our work and play would be altered, as would our view of intelligence, consciousness, and the future of destiny of the human race. At this level, AI systems could pose a more direct threat to human autonomy, freedom, and even survival. After all silicon is cheaper than human life.

In conclusion, we see that AI has made great progress in its short history, but the final sentence of Alan Turing’s essay on Computing Machinery and Intelligence is still valid today:

“We can see only a short distance ahead, but we can see that much remains to be done.”

.

Mehta Ankit Chandrakant
http://www.articlesbase.com/communication-articles/artificial-intelligence-85612.html

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In this day and age, you can’t be too complacent about the safety of your own home. Crime abounds everywhere, and even the seemingly safest areas are not spared. Crime prevention is a near impossible feat. However, crime detection leading to prosecution is not, thanks to CCTV security systems.

CCTV Surveillance Defined
Having a CCTV security system for video surveillance and live monitoring purposes is like having an entire television network devoted to the safety of your home. CCTV security systems may comprise of a single or a group of surveillance cameras on a private in-home network. They can be linked to an observation monitor with well-placed cables or even wirelessly.

CCTV security systems are commonly used in areas in need of high-security, such as banks, casinos, and airports. But because CCTV security systems are relatively inexpensive and simple to use, they are now being used in private homes to bolster homeowners’ peace of mind.

CCTV Surveillance vs. Crime
CCTV security systems rapidly gained popularity as an aftermath of the terrorist attacks on London’s public transport system. Surveillance videos identified the men responsible for the attacks, leading to their capture and eventual prosecution.

This proves that a CCTV security system is an effective tool for crime detection and can provide solid evidence. Furthermore, with constant vigilance, a CCTV security system is a powerful deterrent and may even stop crime before it actually happens.

CCTV Cameras and Your Home
CCTV security cameras are simple enough to be used at home. They can take images with resolutions as high as 1600 x 1200 pixels on a time lapse or motion detection basis, depending on your setup. Some CCTV security systems have add-on features like tilt-zoom, low light, and infrared. CCTV security cameras are relatively inexpensive. Prices vary, depending on factors such as size, type, display, resolution, zoom, and connection. CCTV security cameras are commonly available as domes, bullets, and standard c-mounts. They are available in black and white or colored, with audio or without audio.

With a good setup, CCTV security systems can monitor up to 16 rooms and areas in your home, all the while providing clear and highly visible images. You can monitor your garage, your kitchen, your front yard, and even your mailbox. CCTV security systems are able to record suspicious activities real-time. The cameras subsequently transfer the captured images to a PC or laptop through a USB, coaxial cable, or a wireless adapter.

Study your needs before you install your CCTV security system. Consider the area that you want covered, as well as consider future expansion. If installed outdoors, invest in specialized weatherproof housings and proper protection from vandals. Lighting is also an important thing to consider. The absence of proper lighting will produce muddy pictures that could end up being useless. Lastly, ensure that you have a stable power source and power supply.

CCTV Surveillance and the Law
Video surveillance is subject to privacy laws. Your home is your private domain and you have every right to protect it. A CCTV security system is a powerful addition to your home security system. However, you have to check the legality of your system. It is best to consult with a lawyer or at least get in touch with your local law enforcement department to ensure that all local, state, and federal requirements are met.

Nahshon Roberts
http://www.articlesbase.com/computers-articles/ensure-safety-with-cctv-security-systems-159338.html

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When security systems hit the market, you probably felt pretty secure and thought you were one of the elite who could afford such a system. The problem is that many of these systems are horribly outdated and won’t protect your home the way many of the newer systems will. Perhaps it’s time for an upgrade?

In fact, there are so many new advancements in home security these days that you really don’t want to be stuck with an older system that probably won’t protect you anymore. What about things like keyless entry or even thumb-print entry? Did your old system have something like that? These days, you can really set up your home with the latest technology in security, including wireless systems and home-based hidden cameras. Crime rates aren’t getting any better and having the latest in security systems in your home is a definite must.

One of my favorite new security gadgets is the wireless infrared camera. This system watches over my home, whether I’m at home asleep or on vacation. These kinds of cameras really perform and I wouldn’t be without at least one to guard my home. The amazing thing is that these cameras can be monitored from your laptop computer. Isn’t that unbelievable? There is software available that you can download onto your laptop and it has a link to your home wireless security system. You control everything and can see what’s really going on around the home. If you purchase a hidden wireless camera, you really need to get the computer software, too. It adds a lot to your entire security program.

And what about these other gadgets out there - gadgets like double-layered home window glass, which is lined inside with Plexiglas? Any burglar who attempts a home entry by breaking through a window will be really surprised by the fact that he can’t get through the Plexiglas layer. Your home will be practically impenetrable with these kinds of systems. You can feel extra-secure with a set of those windows in your house.

I personally love the latest camera systems available for use in security. Many of the systems are completely wireless so you can watch almost any part of your house and yard from almost anywhere without the expense and annoyance of wires. I don’t think it’s possible to have too many of these cameras in your home. You can set them up so they see all areas of the house or yard from practically every imaginable angle. These cameras hook up to your laptop or other computer so you could actually be in your workplace while monitoring your home at the same time. It’s almost unbelievable. You can use motion detectors that are situated so that a camera will take an immediate picture of something whenever it triggers the motion sensor.

These new devices are all part of a brand new age in security packages that far outstrip the initial home security systems available even a few years ago. So think about upgrading and go onto the Internet to search the available upgrades for your system. If you don’t see an upgrade you like, consider scrapping the one you have and starting over with a brand new security system.

Joe Goertz
http://www.articlesbase.com/advertising-articles/upgrading-your-security-system-72774.html

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A major legal conflict has begun in Greece over whether the police can use traffic cameras to spy on and prosecute violent demonstrators.
A senior prosecutor,backed by the Conservative government,says the cameras can be used.
But Greece’s privacy watchdog,the Data Protection Authority,says such a move is illegal.
From Athens Malcolm Brabant reports….

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.4GHz Wireless Spy Camera Wristwatch With DVR [ LM-WSC829 ] … Wireless Spy cams spy cameras hidden camera surveillance

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mjelectronics.com protect your home or office with hidden cameras … hidden camera nanny spy dvr ip security equipment

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Not all security camera Digital Video Recorders, or DVRs, are created equal. Remember this as you look for security camera DVRs for your business. There are great DVRs, good DVRs, and DVRs so terrible you cannot tell what you’re looking at.

DVR stands for Digital Video Recorder. It is faster and easier to manage than non-digital and analog systems. Moreover, it provides instant access to recorded or live video. You need not worry about storage, too, because the bulk of video that can be stored on a single disc tremendously outweighs that stored on tape. In fact, a single disc is the equivalent of over 30 VCR tapes. What this means is that you get to economize on space use and costs. The bigger your office space and thus, the more cameras you use, the more you will be able to appreciate the money DVRs can save you.

There are two main types of security camera DVRs, pc-based and stand-alone.

PC-based Security Camera DVR with Video Capture Board

A PC-based DVR is a digital video recorder built like a computer. It may consist of two things: a tower mount or a rack mount. Inside it, you will find a mother board, network card, video card, CPU, hard drive, and memory. The DVR video card and the DVR software give users remote access. The DVR capture board receives video directly from security cameras. The DVR software, in turn, works in conjunction with the DVR board to first, change captured video images into a manageable and recognizable format and second, to provide camera controls, as well as record and playback functions.

Stand-alone Security Camera DVR

A stand-alone security camera DVR is an all-in-one unit. All components of a stand-alone security camera DVR are built on one complete circuit board. Its appearance is very similar to that of a VCR or DVD player. Stand-alone security camera DVRs are highly reliable and are very easy to use and install.

The Difference

A stand-alone security camera DVR is very reliable and user-friendly, mostly because it is built on only one circuit board. One need not worry about system crashes or software conflicts because all the hardware and software are embedded on one board. A PC-based security camera DVR, on the other hand, offer more advances features and are better suited for upgrades and systems expansions. They have bigger CPUs and memory, and you can easily add burners and hard drives.

Stand-alone Versus PC-based

Most heavy and large-scale users, such as banks and airports, opt for PC-based models. Just because they do, however, doesn’t mean you should join in the bandwagon and purchase the same for your office or factory. In truth, you should base your choice of security camera DVR on your surveillance needs. If your company’s camera network is comparatively small and does not require much use of sophisticated controls, then a stand-alone security camera DVR should suffice. If, on the other hand, your surveillance needs require the use of sophisticated controls or if you are planning to expand your company’s surveillance system in the future, then the wisest choice would be a PC-based model.

Here’s another way of looking at it. If reliability and stability are what matters most to you, then buy a stand-alone security camera DVR. If advanced viewing, playback and video file saving over the Internet mean more to you, then go for a PC-based security camera DVR.

Ultimately, what would matter the most is not the type of security camera DVR you purchased but how it protects your business.

Nahshon Roberts
http://www.articlesbase.com/computers-articles/security-camera-dvr-finding-the-type-that-suits-you-136920.html

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With so many security systems on the market today its easy for a buyer to get overwhelmed with the wide selection of systems and options available, not to mention you getting a little bewildered with all the security and technology jargon. One mistake many first time buyers make is buying overly expensive security systems that can be an overkill, that is to say, the system has many features you neither want nor need. One increasing popular and excellent option these days is to buy a security camera kit.

At the heart of a security system kit is a DVR capture card. A DVR card is a digital video recorder (DVR) that records motion video in a digital format onto your PC’s hard disk. To get a DVR based security kit up and running it is simply a case of inserting the DVR card into any spare slot on your PC, installing the included software and connecting the cameras to the DVR card. A buzz word for DVR cards you need to look out for is FPS. FPS stands for Frames Per Second. So with a card of 120FPS and four cameras connected to a system , that translates to recording at a professional rate of 30 Frames Per Second (per camera). The result being excellent detailed live video.

Choosing the actual security cameras will depend on where you want to locate the cameras. There are many different types of cameras to choose from. Indoor, Outdoor, Wireless, Vandal proof etc.

If a camera is to be sited outside it needs to be weather resistant. Outdoor cameras are weatherproof and built to resist the elements.

Dome Cameras are very common in places of high security and surveillance, like a casino or a museum. Like their name, they are dome shaped and fit easily on ceilings. Some dome cameras can even be placed outside the house, but there is a specific type of installation for them. Dome Cameras are one of the most popular of the security cameras, because it is virtually impossible to pin-point what angle the cameras are placed at, unless at close range..

Bullet cameras are named such because they are sold with a bullet like housing. The bullet camera is very small in size and have an integrated design. The length of the lens is very long and is shaped like a stick. Some bullet cameras have a infra-red LED feature. Infrared technology allows a LED light in infrared spectrum which is not visible to the human eye. The light illuminates the viewing area and therefore it is possible to monitor the area even in complete darkness. Depending on the model, these cameras can monitor in darkness up to ten to fifty feet depending on the model. Bullet cameras are weatherproof. They do not have the ability to use different lenses because they are sealed inside the bullet-shaped housing.

Another advantage a DVR kit addresses is that various types of cameras come bundled in your KIT.

Geoffrey Callaghan is CEO of <a href="http://www.saxsecurity.com">www.SaxSecurity.com</a>. Sax Security is a leading supplier of DVR security camera systems.

 

Geoffrey Callaghan
http://www.articlesbase.com/home-security-articles/a-guide-to-choosing-a-security-camera-system-for-your-home-or-business-692706.html

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Digital Cameras have lots of features, buttons, and adjustment tricks all aimed for the sole purpose of capturing great pictures. But what if you’re a newbie and you just want to take one step at a time getting to know your digital camera? Well, I think you’ve found the right place because today we will be discussing simple yet useful tips in ensuring that you will have your money’s worth and the quality of the image you’ve been wanting to achieve.

1. Outdoor Shots

One of the great hidden features of the digital cameras is the fill flash or flash on mode. By taking control of the flash so it goes on when you want it to, not by the camera’s liking or it deems appropriate. In flash on mode, the camera exposes for the background first adding just enough flash that illuminates the subject, thus resulting to an image that looks like taken by a pro.  Wedding photographers and some professionals have been using this technique for years now.

2. Macro-licious

Do you like simple subjects for Photography like the flowers, grasses, or the trees? Then the next time you do, you might want to turn that Macro Mode on (you will see a flower icon somewhere in the buttons) and be surprised to see the world in finer detail. Activate the close up mode on your digital camera and see that even the simplest object takes on new fascinating twist, and the best bit is it is easy to achieve.

3. High Resolution Revolution

One of the most important reasons for having a huge space for memory is to maximize your camera’s capability for shooting the highest resolution. If you paid a premium price for a 6 megapixel digital cameras, then get your money’s worth and shoot at 6 megapixels. And while you’re at it, shoot at your camera’s highest quality compression setting too. The point is, if you have enough memory, then there’s no reason to shoot at a lower resolution and risk missing the opportunity of capturing those great shots.

4. Tedious Tripods

The sight of the photographer using the tripod heightened that professionalism aura surrounding his already intimidating presence, and so they thought. Fact is, the tripod has nothing to do with what makes a true photographer.  But the use of the tripod can really make a big difference between good and badly taken pictures. Problem is, they are bulky, heavy, and frustrating if you’re on a travel. Tripod nowadays comes in various sizes and styles and they cancel the problems with that of generic tripod design (as you already know). 

5. Self Timer Possibilities

It doesn’t mean that you’re branded as the family photographer, you will be missing important occasions and events because by the simple reason of you being the “photographer”. Having the tripod and pushing that “timer” on will save you from that doomed position as the missing photographer. Remember that most built-in camera flashes have only a range of 10 feet (or less), so make sure you don’t stand too far away.

Jake Sanders
http://www.articlesbase.com/photography-articles/digital-camera-photography-tips-and-tricks-731249.html

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