what role is artificial intelligence (AI) going to play in engineering?

 what role is artificial intelligence (AI) going to play in engineering?

Just like with many other industries, artificial intelligence and machine learning are changing engineering. Even though these technologies are now seemingly "everywhere," we shouldn't overlook how truly incredible they are and the remarkable things they enable us to do today and will allow us to do tomorrow. For engineers, artificial intelligence and machine learning might cause the tasks they do to evolve, but it can also help them do things they weren't capable of before.

The field of artificial intelligence (AI) was begun in 1956, but it has been only in the last decade that significant progress has been made to allow the technology to be widely used and experienced by many outside technology circles. Today, artificial intelligence is one of the fastest-growing emerging technologies and describes machines that can perform tasks that previously required human intelligence.

Artificial intelligence that’s used in the engineering sector uses software and hardware components. As machines become more sophisticated, they will be able to support not only smart production lines and complex manufacturing tasks, but will also be able to design and improve tasks over time—with little or no human intervention—through machine learning. Robots have been used by automobile manufacturers on the production line for quite some time and have gone from completing simple engineering tasks to now handling many precision moves required for some of the most intricate parts of the process.

Many of the tasks engineers are responsible for, such as design and simulation, can be enhanced with the support of artificial intelligence tools. Consider how Computer Aided Design (CAD) was once just a supplemental tool to engineering, and today it is a fundamental part of the daily workflow. These tools will help improve the capabilities of engineers and make it possible to explore design and weight-saving options that weren't ever possible before.

Another way artificial intelligence can support engineering tasks is to break down silos between departments and help to effectively manage data to glean insights from it. AI programs can provide automation for low-value tasks freeing up engineers to perform higher-value tasks. By using machine learning to discover patterns in the data, machines will be incredibly important to help with engineering judgment.

Artificial Intelligence, Some important facts

Artificial Intelligence, Some important facts:

• 1.Artificial intelligence is an expansive branch of computer science that focuses on building smart machines.
• 2.American computer scientist John McCarthy coined the term artificial intelligence back in 1956.
• 3.Artificial intelligence and robotics are two entirely separate fields.
• 4.The four artificial intelligence types are reactive machines, limited memory, Theory of Mind, and self-aware.
• 5.Other subsets of AI include big data, machine learning, and natural language processing.
• 6.Artificial intelligence examples include Face ID, the search algorithm, and recommendation algorithm, among others.

The words artificial intelligence may seem like a far-off concept that has nothing to do with us. But the truth is that we encounter several examples of artificial intelligence in our daily lives.

From Netflix‘s movie recommendation to Amazon‘s Alexa, we now rely on various AI models without knowing it. 

How to Make Vermicompost

 

How to Make Vermicompost | How To make Vermicompost at Home From Kitchen Waste

Vermi-composting, that is composting with worms is super easy and great for plants. All you need is a box that you put some worms in and some organic material. One can keep them inside the house (the smell is not a problem), so they are always at a comfortable temp. If you keep them outside, just pay attention to keeping them out of the sun when its hot and in the sun when its cold, that’s probably enough, depending on where you live.

To make a worm bin you need two plastic bins. One bin sits inside the other, and has some small holes drilled in the bottom so water can drain from the compost into the second bin.

The first bin don’t actually do anything to, except put some kind of spacers at the bottom. Here put some small old Tupperware containers but just about anything will work, some scraps of wood, small coffee cups just about anything you can think of. This is just to create a space that excess water can collect.We only need one lid for the system, and want to cut some holes to allow the worms to breathe.

Having a lid like this helps keep the smell down if you keep your worm bin inside. Drill a few holes in the lid, then covered it with landscape fabric, the stuff you put under rocks and mulch to keep weeds down. Just about any kind of fine netting should work fine, this is just to keep the worms from escaping.  Keep it in the basement and or below the portico  never you will be been able to smell bad.

Get the worms from any near by nurssery or there’s no reason you can’t collect your own worms if you do a little bit of digging, especially shortly after a rain, you want red wigglers or earthworms.

You can put just about any organic material in the bins, but don't use meat or dairy. you may have also heard that citrus is bad, don't use it.

After a few months the worms will have reproduced and number in the thousands. They will produce wonderful compost in much less time than a normal pile. 

 

Artificial Intelligence in Sleep Medicine

In recent years there has been a rapid emergence of artificial intelligence (AI) in the field of sleep medicine. AI refers to the capability of computer systems to perform tasks conventionally thought to require human intelligence, such as

Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. There are three main areas where sleep medicine benefits from AI. 

➤The first application is modernizing the scoring process of polysomnography (PSG). Currently, the sleep technologists play a major role on judicating the 30-second sleep epochs as awake or asleep and/or the stage of sleep. The AI has potential to improve this lengthy process, and expedite sleep reports.

 [polysomnography (PSG) Meaning➤a type of sleep study, is a multi-parameter study of sleep and a diagnostic tool in sleep medicine. The test result is called a polysomnogram, also abbreviated PSG]. 

➤The second application of AI in sleep is leveraging the longitudinal data accumulated within electronic medical records (EMR). Sleep medicine is primed to benefit from AI used in population health research. Researchers have successfully leveraged “big data” to offer new insights into sleep physiology, improve the accuracy of diagnosis of sleep disorders, predict response and adherence to treatment, and use sleep parameters as predictors of future physical and mental health. This leads to treatment optimization and personalization. 

➤The third application of AI in sleep medicine is the use of wearable sensors. The wearable sensors show promise in tracking health records and linking several digital biomarkers to the overall health condition of patients. They provide an opportunity to elevate the traditional EMR to the new level of electronic health records (EHR) by measuring several parameters and synchronizing multilevel bio-potentials and health time series.

These applications will likely become more widely available, empowering people to improve their sleep, through the possibility of better understanding their sleeping patterns. Ultimately this can result in a reduction in sleep health disparities.

The goal of this research topic is to inform advances in the use of artificial intelligence (AI) in the field of sleep medicine.

Topics of interest include (but are not limited to) Artificial Intelligence and Machine Learning related to:

1. Assisting and enhancing polysomnography scoring
2. Supporting clinical decision
3. Providing new insights to inform the clinical care of sleep disorders
3. Leveraging the electronic medical records (EMR)
4. Managing and monitoring population health
5. Advancing our understanding of the integral role sleep plays in human health
6. Harnessing the potential of wearable devices (i.e. wrist actigraphy) into sleep medicine
7. Integrating wearables devices into EMR for remote health monitoring and at-home health application
8. Understanding and addressing sleep health disparities