IGCSE Computer Science (2026-2028): C6 - Automated System, Robotic & Artificial Intelligence

0:00 hello everyone welcome back to this channel so in this video we're going to learn about igcse computer science chapter 6 automated system and emerging technologies which basically covers the current trend or in the computer science field so this chapter can be subdivided into multiple different topics so such as the automated system we'll start off with that and proceed to robotic and lastly we will cover some um ito up with artificial intelligence which can be further branch out to expert system and machine learning so let us first start with automated system and or the definition of it is that it is a combination of software and hardware that is designed and programmed

0:46 to work look at this keyword automatically without the need of any human interventions so as compared to the hardware devices that we learned in chapter 3 automated system is a computer that doesn't require human intervention so for instance i'm using this stylus here it is an input device and i use it to interact with my ipad so in other words i need to adjust this manually to write something on my ipad so this is not automatic automated system work in a way that doesn't require a human to do anything so there are three hardware components that are important to allow automated

1:32 system work so first of all we have the sensor which is also known as the automated input it's an input device that takes the reading from the surrounding and then it will send data to the microprocessor before we talk about microprocessor just note here is that every value that is captured by the sensor if it is an analog data such as temperature density it will first need to be converted into digital formats which means it needs to be converted into 0 to 1 0 and 1 because binary is the only language that the computer can understand all right so the second component that is needed is called the microprocessor

2:17 so this microprocessor it will pre process the input from the census and if necessary it will send instruction to other components such as actuator it is basically a middleman that process the data sent by the input device the census before deciding to do anything with it all right so third component which is important is the actuator it turns the electrical thickness from the microprocessor to output such as movement all right turning on the wave rotate the steering wheel it it still kind of sounds that strike to explain it in this way so i figured that i better explain some of the applications of automated system to help you get a glimpse of how this is useful

3:02 in the real world so there are seven applications um which is not exhaustive but apparently in our syllabus we only covered seven so the first application of the automated system is transport such as autonomous car note that i have underlined the three components that are important in the system such as we have sensors here actuators and microprocessors all right so for autonomous car like the one that is launched by tesla how it works is that they use a sensors attached to the car to act as a eye and ear for the car to detect what is happening around surrounds in the surrounding

3:49 and then the sensor would then send all this data to the microprocessors to know what to perform next and then the actuator will then perform the followings depending on what is being detected by the sensors okay so here are some of the disadvantages and disadvantages um when we learn all this thing we need to know that they they are good they are good technologies but there is also certain risks involved in using them for for instance the advantages of an autonomous car would be it is a lot safer because the microprocessor can calculate exactly how much you have to turn the steering wheel or how much you need to accelerate and it's also better for environment

4:34 because vehicles will operate more efficiently there wouldn't be a few way stage but there's also some disadvantages associated to this first of all it's quite expensive because it involves computers and also the ever-present fear of hacking into the vehicle control system just imagine that the hacker hack into your car's computer and it just do whatever that is not supposed to do and it's kind of um causes some um criminal activity so here are some of the advantages and disadvantages of using automated system and the transport industry so next up we also learned that automated system is also used in agriculture such as automated harvesting of crops

5:22 so the sensors could detect what is the optimal times for harvesting based on factors such as weather condition um so what is how is this different from human is that we human tend to make mistakes we tend to make wrong judgment but computer is a lot more accurate in it that they can in the long term it could benefit this human by making less errors and then the microprocessors will using the value from the sensors determine where exactly should you do the harvest things and the actuator will will be used to carry out the extraction of goods from the ground so um here are some advantage pages and disadvantages which is um

6:07 the delivery of chemicals can be as i said machines are very accurate everything is works according to formula so they know exactly how much pesticide and fertilizers to be used and this ensures that the farming can can be successful and some of the disadvantages that it result in fewer job opportunities because when you use automated system in your farm you wouldn't need to hire so many people all right so the third application of automated system is weather forecasting it helps to especially in the airports to predict poor flying and landing conditions so census again very much like the agriculture it checks for potentially dangerous weather they

6:53 measure the humidity to measure the wind speed and these data will then be sent to the microprocessor to issue relevant warnings as a result of get data gathered and actuators can be used to activate emergency systems such as lightning and whatever required so advantage is that information about the overhead weather condition is constantly fed to adequate traffic controllers because weather can be different seconds to seconds so it's better that we detect them earlier and faster instead of using human and prediction can some of the disadvantage is that it can be inc accurate especially if snow is forecast and

7:39 it ultimately doesn't arrive all right so the fourth application of automated system is gaming so basically um let's say sensors here are built into the game environments where characters interact with human controllers and then sensors microprocessors will use this data to determine game outcome and decision actuators are activated in controller to give haptic feedback such as vibration if you look at the current ps5 controllers it actually has something called adaptive touch which means it provides different senses it stimulates your senses when the game is in different phases all right so the advantage is that the depth of gaming challenges increase

8:25 with computer-generated opponents and behave in a more human way and the disadvantage is that it decreases via social interaction with other human so this is a bit like disadvantage of gaming than the automated system all right so um the fifth application is the lightning um we discussed this in chapter 3.6 when we talk about sensors the sensors basically basically detects how much light you stand in the surrounding and the microprocessor run routine based on human requirements so this is the keyword here when the microprocessor process this data um the rule that they use is actually determined by us human which means they are they could be a bunch of code written by programmers to tell the

9:11 microprocessor what are the conditions for this action to be launched all right so there's another node and then after the microprocessor process the data it will send the signal to actuator to activate certain home equipment turn on the like and so on so the advantage is that system can be taught to react to environmental factors such as switching like on and off when the conditions are correct and also it can become complex because it's not like traditional speech and these light bulbs um the smart bump can also be expensive to maintain so not everyone needs it not everyone's needs these high-tech stuff therefore they could have saved some money if they don't use it so um followed by science the last

9:59 application automated laboratory experiments i personally have not used it but what i say here is that how it works is sensors detect changes in the environmental conditions such as humidity and microprocessor will then calculate how many alterations need to be applied to the experimented settings then the actuator can do things according to the rules such as turning on heater cooler and water supplies as required so the advantage of using automated system and science in experimental settings is that more experiments can be repeated and reading of data can take place when the human carryout tests test manually which means it can be

10:45 repeated as a faster speed because everything is automated but here is the disadvantage is that if something goes wrong it can this error or before this is discovered which could ruin any result um collected because human is not there and the computer is not smart enough to detect if something goes wrong so this is all about automated system it basically consists of three important components such as sensors microprocessors and actuator and we also learn about the various applications of of it in the real world so next up we are going to look into robotics all right robotic is a little bit different as compared to automated system

11:32 so let's look at what robotic actually is so the border is the sas language which means forced labor just some fun fact about the origin of how the word robot comes up so the definition of robot robotic means the design here is a constructions and operations of robots that are used to enhance our working and personal life so here i will explain the three characteristics of a robot and then having learned these three characteristics we'll be able to know whether an object or technology is considered robotic or not so first of all a robot will have

12:19 electrical components such as the one that we learned just now in automated system the sensors a microprocessor and actuator in other words with robots they are part of automated system but not all automated system are robot so again sensor sense the surrounding microprocessor process the data and actuator do the work um second thing about robot is that it will have mechanical structure so it should be a machinery that has a movable part they can make use of wheels cause piston gears to carry out functions such as turning twisting moving backwards and forward gripping out lifting um i know it's a little bit hard to understand what a mechanical structure is

13:04 you definitely learn more um in the next few minutes when we talk about uh a robot in factories and the application of it so the third characteristic of a robot is that it is also programmable which means we can insert codes into these robots to tell them to to teach them the rule of handling the input data all right so these are basically have a controller they act as a brain to determine the action to be taken to perform a certain task and these controllers just like the human brain it requires input data um and but this controllers are programmable to allow robots to do certain tasks

13:50 so here we have a quiz here based on the definition of a robot do you think that a chatbot is a robot so the tree um characteristic of a robot is that it has electrical components mechanical structure which means it has to be a machinery and it's also programmable then it's a chat box it's a chat box okay your c answer is a chat bot a robot the answer is no because a chat bot that we use day to day they don't have any mechanical structure all right so these are also known as the software robot they are different compared to hardware robots in the sense

14:37 that they don't have any machineries and here what they say is that software robots are not robot as they don't have the above characteristic so um additional knowledge here is that we have two different types of robots one is called the independent robots which means they are pretty much independent and don't require human to control them such as autonomous vehicle you know in a permits bus obviously you don't need a bus driver right and as for dependent robot is they have a human who is interfacing directly with the robot all right which means human control the robot so um

15:22 to again just like automate a system to explain better the how useful robotic is i have a few pictures to show the applications of robotics in the real world in the industry so if you look here this is a robot in the car industry car factory all right um so this is one of the usage instead of human assembling the car they actually put the car owner purchased all this machinery to do the work and the advantage of it is that the robot can work in a condition that may be hazardous to humans they don't need you know good action good environment they can work in any environment basically

16:08 and they can work all the time without the need to stop they can't carry it out they don't need rest however disadvantage just like what we mentioned just now robot can also lead to higher unemployment amongst manual labor tasks because they essentially can do what humans can do and also there's a risk of de-skilling when robots take over certain tasks which means humans don't actually know how to do this thing anymore because they are all done by human i mean they are all done by robot so this is one application of robotic and industry let's look at the transport we talked about this an automated system the autonomous car for princeton and tesla and also the rovers that uh that

16:53 is currently on mars so these are how um robotics is used in the transport system um the advantage is that it's safer and better for the environment but they are they can also be very expensive to set up all right also the ever-present sphere basically the same thing that we talked about in automated system so in agriculture so if you look at this robot here they are hover stink so instead of um i don't really see human here in this picture everything is operated by a robot so they can replace slow and repetitive tasks to allow farmers to concentrate on how to improve production u so one thing i want all of you to understand here is that even though

17:39 robotic seemed to have taken some of the human tasks one of the advantage of having all this automated system and robotics is that they free up time for us humans to think about the the creative part of the business and also the the task because if you think about it all these things are repetitive and they are pretty boring and they don't require a creative mind to harvest so if we delegate all these tasks to the robot we can have the additional time to think about um new invention to be more innovative so this is some of the advantage that you should um think about when we talk about automated system and robotic

18:26 so um the advantage is that they are very accurate in terms of delivering the chemical and again what i said disadvantage fewer job opportunities so um next up in mexican medicine here they said robots can also be used in surgery i couldn't find a picture on it but what they do is that these robotics are used to monitor fighter live data in research and development such as tissue engineering all right such and such and they can also take blood samples from the patient it is less painful um what they say here is that robot can spot um vein better perhaps sometimes better than human so that the patients can be

19:11 can feel less pain and the advantage is that surgery can take less time which improve the chances of recovery for the patient and the disadvantage again is that it is expensive so last but not least in domestic which is how the project is used in our home right like um we have vacuum cleaner and land movers so um this is a vacuum cleaner the image here so if you have a vacuum cleaner at home you basically don't have to do work you can delegate it to them all right the advantage is that robots can quickly learn the environment whether there's dust in front of them or in the room and they can be programmed to work at convenient time and the disadvantage they can encourage a little

19:57 sedentary lifestyle which means um you just sit down all the day and not do any work so entertainment um for now oh robot is also used in the firm industry so this is one of the youtuber that i like a lot called mkbhd um he has this video about how robotic takes over his bombing process so um the advantage of it is that firm can be presented in a way that humans would not be able to normally see due to robotic technologies again fewer job opportunities you don't need photographer anymore and human increasingly replaced by machinery so um i have a positive question here which asks

20:42 about robots so if they are if we do ask you this question two other characteristic of a robot remember a rubber has to have machinery structure electrical components they have to be programmable so these are the three things that we know and also they ask two advantages of using robots again it is more accurate and it's safer so if you look at the marketing scheme so these are the answers that you can write in if you are you face these problems in your ig saves the exam so that's the end of it so so next up we are going to learn about artificial intelligence so which is one of the hot topic in the computer science field

21:28 but before we look into what ai is let's first define it the definition of ai is a branch of computer science dealing with the simulation of intelligent human behavior by a computer the key word here is simulation essentially ai aims to instill the human intelligence into a computer what is exactly intelligence if you search up google you will get this answer is the ability to think to learn from experience to solve problems and to adapt to new situations and ai aims to have the computer learn all these things so another way to explain it is that um

22:13 we can look at how human behavior works so for instance if you are planning out a hangout with your friends this could be your thought process all right so you might ask okay who is going with us and what's their hobbies okay and then you ask further questions to know where to plan the hangout and who to go out with so when we talk about artificial intelligence we basically want the computer to have all these thoughts processed inside their memory all right so we're essentially instilling our thought process into a machine so first of all let's look at how an ai reason based on the data they

23:00 receive how do we inspire such intelligence into a computer which is in non-living things so i've outlined three methods here based on the textbook first of all is that they draw a reason conclusion based on a given data here i have an x y exists on the relationship between the square feet of a house and also its price and each point here is a data point a data point i need to use another color a data point so let's say we want the computer to predict the price of a house based on the square meter attribute we have we have the data here which is the house is

23:47 around 800 square feet and using the data here other data the historical data we can actually predict how much would this house cost in other words the computer can do the same too too um even though it's out of a syllabus i just mentioned it here um this method is called linear regression is a model in machine learning that basically draws a line of best feet based on the existing data and then using this line we are able to predict how for instance in this case we are able to predict the price of the house based on the square meter so the first method that ai used to

24:34 do reasoning is based on the given data historical data so um however not everything can be predicted using past data so sometimes they do need to learn some rules so uh in this case um i draw this example here how do we detect someone has copy positive basically we ask question like does he cough does he has fever does he has close contact all right so just like how we can think in this way we can teach the machine to think in this way too so we can teach them to ask certain questions as i will show an example later on in a sentence detection system

25:20 by teaching machine how to learn all these rules it will be able to predict whether a person has this disease or not and also in many other applications so we basically up teach them certain rules so next of all next up ai can also quickly descend patterns like us human and then make predictions by adapting to the new data so for instance this is your um the bank account input for a certain month so if out of nowhere um maybe next week the transaction exceeds the normal average the computer will be able

26:06 to detect it based on the historical data and inform the company that hey something is not so wrong maybe the bank all right we can teach the aitd certain patent based on historical data so here are the three methods all right so there are two different branches of artificial intelligence the first one is expert system and the second one is machine learning let's just first look at expert system expert system is basically a computer system that mimics the decision-making ability of a human so it stimulates the judgment and behavior of a human or organization that has expert knowledge and experience so one type of expert that i believe

26:52 everyone knows doctor when you see the doctor you just tell them what is the symptoms and using their medical knowledge they will be able to tell you what disease you have so what computer sciences has come up with is the ability to teach the computer this knowledge and then ask the computer to use this knowledge to act like an expert so let's look at um i have opened up a page called symptoms tracker which is an example of expert system here basically you just have to type out all your symptoms just like how you would tell doctor your symptoms and they will tell you

27:38 what are the possible diseases that you have so let's try it out um let's say i have fever so yeah versus one cuff and what else um dire okay um cardia okay i just simply type in some of the symptoms i don't understand what they are but i'm a male my age is this category and i'm from asia east asia southeast asia so having submitted all these things um when i click the summit button oh man and this symptom checkers will show me

28:25 all the diseases that has that i might have all right lung cancer influenza bronchitis and i i can even look up more on this um symptoms so reflex so these are all the things that i might have based on the symptoms i submitted so feel free to check try that out yourself i will include link in the video description so let's continue on the structure of an expert system first of all just like the app that we see just now every expert system should have a user interface which acts as an interface for human to interact with the expert system so that we can use them and it also should also have something

29:10 called the knowledge base in which i stole all the knowledge about an area of expertise obtained from a number of expert sources so for the symptoms checkers that we use just now the knowledge could be the medical knowledge done by medical researchers all right so for rue base it should also has certain rules used by the inference engine to draw a conclusion for instance and the patient tracker symptom checker that we used just now they could have rules like if you have this sentence and this sentence together you would yeah possibly having these diseases so we also should have the inference engine which is the part of the expert system that makes

29:55 decision based on what they have from the knowledge and the rule base and produce a possible solutions to a problem so last but not least is the explanation system all right so the expert system can make all the possible guesses but it if it fails to it communicate with it with the user then it doesn't really have any usage so the explanation system could suggest certain actions for the user to take um it could also provide the accuracy of its prediction so for instance instead of saying you might have covet it's quite vague to say something like that the computer system can say something like you have a 75 chances of getting kobit 19. so

30:44 that's the explanation system part from an expert system so these are the five struck components of an express system remember this so here are the example for medical diagnosis knowledge base could be a library of symptoms relation to disease and if they have multiple symptoms suggest resistance is done by the rule base and also suggest possible disease and action steps explanation system and for scheduling delivering service like your amazon shoppie how do they decide which route to take so the knowledge base could be the number of route passes and delivery points so rule base could be if there's a

31:29 traffic jam don't pick that route explanation system suggests the best route to take diagnosis of breast cancer mammography with all types of cancers and normal mammography this is in fact one of my final year projecting university in which we collect a bunch of mammograms and then use that to train our models to decide whether a new input has the new mammogram is a cancer image or a non-cancer image so ruby's if you watch sports i observe categorize as cancel predict probability so this is some of the image that um we can feed into the system so other examples of expert systems here i have a list here you can feel free to

32:15 have a read like bank loan approval system mineral perspective so instead of having an expert doing all these things to us we train the computer to become an expert to help us to do stuff so here are some of the advantages and disadvantages of expert system they are have high level of expertise high accuracy consistent result because they don't involve emotions and have the ability to store vast amount of ideas and facts you just increase the hard drive they have very fast response time the disadvantage will be the setup and maintenance costs again it's all about money they are only as good as the information entered into the system so that's the advantages and disadvantages

33:01 so let's look at the second category of artificial intelligence which is called machine learning it's a little bit different as compared to expert system because they don't have a lot of rules instead they use data points to create models and using that models and a result can be predicted so let me give you the definition before i explain so machine learning is the science of training computers with sample data with sample data so that they can go on to make predictions about new unseen data without the need to specifically program them for the new data so algorithms are trained and learned from their past experiences and examples they don't need to be specifically programmed

33:47 this is the key part they don't need of course they need certain programming but they don't need rule-based programming like if hours and stuff this is the key and they can make predictions about new unseen data and an example would be how the email company like google they can create an app that automatically classified an email into spam so we have this email here blah blah blah congratulations all right how do we teach the machine that this email here is a spamming meal we kind of have rules like oh if they have this word million in it then they have they are considered spam

34:33 it's very hard to come up with rules that are able to classify all the spam email so the intelligent computer scientists come up with a way that teaches the computer how to do this so first of all a machine learning algorithm collects data about email all right they carried out the cleaning process to remove the stock work for instance if this is the email that you receive here all right you receive this this is the original email there will be they will first remove it's called um remove the stop words which means the frequently appeared word like the and and a because they don't contribute they can't help us to determine whether an email is spam or not and after that

35:19 these words that are frequently used in email that could indicate the incoming email is very likely to be spam so what they're saying here is that they collect data about all the words that appear frequently in the spam even and then using the data the machine learning model is built and the training data set is used to train the model and make it using past emails known to be spam which means they take in thousands and millions of spam emails and using the information they kind of train the computer to know when to categorize an email as a spam email and when to classify it as as a normal email so once it is evaluated the model is fine-tuned and tested live

36:06 and it's pretty hard to explain it and simple terms but just remember that the term machine learning means we give the machine a tons of data so that once they have enough data set they will be able to use the data set they will learn themselves what is the rule for spam email and non-spam and by using the knowledge the machine can learn how to categorize images in spam and not spam so another application of machine learning there are tons of them but one of them is auto tech and a photograph i believe it's also available in apple photo library in which they will auto attack a person by recognizing

36:52 phases and suggest name suggest name because how it works is that they look at all your photos in your library and then they try to identify dissimilar faces and this is how auto tech work the other example example that is very impressive is called alphago they basically create and a machine learning algorithm that knows how to play the chess game go and again how it works is that they just feed the algorithm tons of matches on tons of gold matches and the machine will then use the knowledge to know what is the best move given a

37:38 certain scenario in fact this alphago machine even beats the world champion listedo in in the match all right i will link this documentary in the description below to help you understand better what is machine learning so here's the difference between expert system and machine learning that expert system here they are rule-based system which means they um functions by having many many rules while modern machine learning are based on statistical modeling of data so they could be using um different machine learning models such as linear regression um decision tree so these are some of the machine

38:24 learning models that are used by machine learning engineer in fact there's a course to teach all about that from andrew ung in stanford university if you're interested you can check it out so in other words we can say that expert system use a lot of if then statement if they this data if this scenario happens then i suggest this outcome whereas the machine learning system projects the input into some model spaces they create different machine learning model and by using the model they predict the outcome for a given scenario so that's the end of it we learned in artificial intelligence that is expert system and also the

39:09 machine learning and how they to work together this is a relatively brief session if you wish to know more i definitely recommend you to search up youtube or cara to learn in depth how these machine learning models work in fact they are very interesting and very complicated so that's the end of this video and this chapter i hope you learned something and thank you for watching goodbye everyone