The Defense Advanced Research Projects Agency (DARPA) started the research and development of automated visual surveillance and monitoring (VSAM) program, between 1997 and 1999, and airborne video surveillance (AVS) programs, from 1998 to 2002. Currently, there is a major effort underway in the vision community to develop a fully automated tracking surveillance system. Automated video surveillance monitors people and vehicles in real time within a busy environment. Existing automated surveillance systems are based on the environment they are primarily designed to observe, i.e., indoor, outdoor or airborne, the amount of sensors that the automated system can handle and the mobility of sensor, i.e., stationary camera vs. mobile camera. The purpose of a surveillance system is to record properties and trajectories of objects in a given area, generate warnings or notify designated authority in case of occurrence of particular events.[70]
Set up and manage your factories, expand your production capabilities and improve your cars by investing into research and development to get an edge over your competition. High quality cars and good quality assurance might cost a fortune, but may pay for themselves in the long term. Like in real life, in Automation car design and marketing is full of compromises.
Full automation commonly defined as requiring no control or very limited control by the driver; such automation would be accomplished through a combination of sensor, computer, and communications systems in vehicles and along the roadway. Fully automated driving would, in theory, allow closer vehicle spacing and higher speeds, which could enhance traffic capacity in places where additional road building is physically impossible, politically unacceptable, or prohibitively expensive. Automated controls also might enhance road safety by reducing the opportunity for driver error, which causes a large share of motor vehicle crashes. Other potential benefits include improved air quality (as a result of more-efficient traffic flows), increased fuel economy, and spin-off technologies generated during research and development related to automated highway systems.[71]
“If you need a framework to test web services, you may use a different set of tools within a framework,” says Jones. “You should be able to combine tools within a framework in a way that allows you to test, so you are not limited to just UI, integration, or web-services testing. Build your framework in a way that supports a range of testing goals.”
Monitoring apps can provide a wealth of information about your home, from the status of the current moment to a detailed history of what has happened up to now. You can check your security system’s status, whether the lights are on, whether the doors are locked, what the current temperature of your home is and much more. With cameras as part of your home automation system, you can even pull up real-time video feeds and literally see what’s going on in your home while you’re away.

Jones recommends flexible automation frameworks and cautions against using a framework limited to only UI testing, for example. Some test teams build their frameworks from scratch to satisfy the desired result of the test automation code and activities. According to Jones, most test automation initiatives fail due to the poor design of the test automation framework architecture for that project.


Successive development cycles will require execution of same test suite repeatedly. Using a test automation tool, it's possible to record this test suite and re-play it as required.Once the test suite is automated, no human intervention is required.This improved ROI of Test Automation.The goal of Automation is to reduce the number of test cases to be run manually and not to eliminate Manual Testing altogether.
Hazen uses the term “automagic” to get people to think about what their goals are for using automation tools and technology for their specific project needs. He cautions against assuming the use of automation testing tools is a cure-all or silver bullet solution. As Hazen points out, automation testing is still dependent on the people performing the testing.
I am a big believer in tracking fitness progress. Doing so not only keeps you motivated, but it can also help you make sense of what is working and what is not. People are constantly on diets, trying to lose weight or gain muscle. But how do you keep track of your progress? Assuming you made progress because of the time you spent in the gym or simply listening to your body may not be the best method.
TestLeft is a powerful yet lean functional testing tool for dev-testers working in Agile teams. It fully embeds into standard development IDEs enabling developers to easily and quickly create robust functional automated tests without leaving their favorite IDEs such as Visual Studio. It also works well with other tools in dev eco-systems such as source control or continuous integration systems. With TestLeft, developers can:
He prefers to use the term “automated test execution” when discussing test automation because the majority of people are referring to automating that activity in the testing process. Non-technical testers should have access to the automation tools. Today’s modern automation technology makes it possible for teams to collaborate and benefit from automated testing.  
There's plenty of failure in that combination. First of all, the feedback loop from development to test is delayed. It is likely that the code doesn't have the hooks and affordances you need to test it. Element IDs might not be predictable, or might be tied to the database, for example. With one recent customer, we couldn't delete orders, and the system added a new order as a row at the bottom. Once we had 20 test runs, the new orders appeared on page two! That created a layer of back and forth where the code didn't do what it needed to do on the first pass. John Seddon, the British occupational psychologist, calls this "failure demand," which creates extra work (demand) on a system that only exists because the system failed the first time around.

Testing as a craft is a highly complex endeavour, an interactive cognitive process. Humans are able to evaluate hundreds of problem patterns, some of which can only be specified in purely subjective terms. Many others are complex, ambiguous, and volatile. Therefore, we can only automate very narrow spectra of testing, such as searching for technical bugs (i.e. crashes).

Like BPA, RPA can reduce human error and the cost of employing a large staff. Bots do not require custom software, and they are fairly low cost and simple to integrate. According to McKinsey & Company, the return on investment for RPA varies between 30-200 percent in the first year, mainly in labor savings. One company in banking was able to add 85 bots with the capacity of 200 staff members, cutting its recruiting cost by 30 percent.


David Autor, an economist at MIT who closely tracks the effects of automation on labor markets, recently complained that “journalists and expert commentators overstate the extent of machine substitution for human labor and ignore the strong complementarities that increase productivity, raise earnings, and augment demand for skilled labor.” He pointed to the immense challenge of applying machines to any tasks that call for flexibility, judgment, or common sense, and then pushed his point further. “Tasks that cannot be substituted by computerization are generally complemented by it,” he wrote. “This point is as fundamental as it is overlooked.”


Suddenly, it seems, people in all walks of life are becoming very concerned about advancing automation. And they should be: Unless we find as many tasks to give humans as we find to take away from them, all the social and psychological ills of joblessness will grow, from economic recession to youth unemployment to individual crises of identity. That’s especially true now that automation is coming to knowledge work, in the form of artificial intelligence. Knowledge work—which we’ll define loosely as work that is more mental than manual, involves consequential decision making, and has traditionally required a college education—accounts for a large proportion of jobs in today’s mature economies. It is the high ground to which humanity has retreated as machines have taken over less cognitively challenging work. But in the very foreseeable future, as the Gartner analyst Nigel Rayner says, “many of the things executives do today will be automated.”

A company that appears to be run by a pro-Trump conspiracy theorist offered to pay women to make false claims against Special Counsel Robert Mueller in the days leading up to the midterm elections—and the special counsel’s office has asked the FBI to weigh in. “When we learned last week of allegations that women were offered money to make false claims about the Special Counsel, we immediately referred the matter to the FBI for investigation,” the Mueller spokesman Peter Carr told me in an email on Tuesday.
What does this mean for us? Hello, free time! It means we would have more time to spend doing things that a machine just cannot do. You’ll get to focus on the creative aspects of your job. Let your brain actually do some thinking and innovating. As much as I hate to sound scientific, you’ll be able to let your human-like capabilities flourish to prove your value. This is where the three job categories that will thrive with automation come into play: creatives, composers and coaches will start to take off.
IBM helps clients around the world transform and manage functional and industry-specific processes to achieve intelligent digital operations. These services rely on AI, process automation and advanced analytics to help deliver higher quality processes at lower cost with less risk. IBM process automation services address the four fundamentals of process design.
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