AI, automation and IoT: Technologies that have had the maximum impact on computer science engineering 

Introduction 

Computer science engineering can be regarded as a hotbed for testing and development of new technologies. As technology continues to advance, so does research in Computer Science Engineering continue to accentuate. This intricate relation between the development of new technology and management of computer science engineering has led to the technological revolution that we are currently witnessing. 

The stakeholders in this technological revolution are numerous. Businesses have played their part very well, the government has set the appropriate policy framework and academic institutions are not behind in this race. If we take a look at any college for MCA in the country, we find that great importance is given to the prospects of research and development related to computer science engineering. Perhaps, the academic sector has understood that the way to keep up with the rapid technological progress is to experiment in new technologies related to computer science. In this article, we take a look at different technologies in Computer Science Engineering that have had a great impact in the present technological revolution.

The age of artificial intelligence 

The age that we are currently in is regarded as the age of artificial intelligence. In simple terms, Artificial Intelligence can be regarded as the replication of human intelligence by advanced machines. When machines become so advanced that they mimic the functioning and capability of the human brain, we say that they have acquired machine intelligence. This also points out to the fact that machine learning is the operating arm of artificial intelligence. 

Machine learning operates on the largest data sets possible and understands the functioning of different processes. By understanding various datasets, machine learning and artificial intelligence make sense of these processes. A short-term and a long-term memory is developed for various processes so that previous conclusions can be used for predicting future outcomes. The capacity to store previous tasks and the capability of computers to predict future tasks is beyond the capacity of the human brain. This means that the human brain has a limited capacity for storing information but this capacity is unlimited for machines. 

Machines can not only use different rules for deriving definite conclusions but can also use previous results for self correction processes. This capacity of machines has allowed them to access, analyze, process and visualize data bases and diagnose data with a lot of ease. The applications of Artificial Intelligence and machine learning are grounded on this computational power of machines.

The process of automation 

The process of automation involves the continuous operation of different processes with minimum human involvement. In the age of industry 4.0, various tasks are being carried out by machines on their own. The erstwhile tasks that required human inputs are now effectively being handled by machines. Gone are the days when humans needed to monitor the functioning of machines so that operations remain error free. In the present time, machines have the power of self correction, self regulation and self improvement. 

If this was not enough, we have come to a stage where we monitor the functioning of different machines with the help of other machines. This has completely wiped out the involvement of humans from different types of automation tasks. In the present time, the automation capacity is so much developed that a lot of human resources have been freed and which can now be deployed for other prospective processes like organizational management and decision making.

Operating with IoT

The most awaited technology that has created a buzz in the technological sphere is the internet of things. In simple terms, the internet of things can be defined as an ecosystem of interconnected devices and gadgets that communicate with each other. In this way, the internet of things operates as an organic entity in which each device is aware of the functioning of other devices. 

The aim is to make the entire ecosystem of smart devices to function in a synchronous manner. This ecosystem not only comprises variable lighting solutions, smart devices and sensors but also buildings and vehicles. This gives an idea of the large platform that is covered by the internet of things. The aim of the internet of things is to speed up the process of automation and catalyze the process of operations. 

The data pipeline that runs across the IoT network records, analyses and interprets data that has a great value associated with it. This data which is generated from IoT devices is invaluable for different companies. 

The way ahead 

The platform that has been laid down by computer science engineering has triggered the current digital revolution. This revolution would be accentuated by other application oriented processes like autonomous vehicles, drones, chatbots, virtual reality, augmented reality and big data analytics.