Artificial Intelligence is changing how different business sectors operate, from customer service research on data to operations.

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Artificial Intelligence is changing how different business sectors operate, from customer service research on data to operations.
Artificial Intelligence is changing how different business sectors operate, from customer service research on data to operations.

Artificial Intelligence (AI) is now an integral part of our lives via algorithmic search engines or using Siri and Alexa on mobile phones to translate taxi requests maths calculations.

Businesses are making huge strides to adopt AI in their everyday activities. According to Gartner, Inc, the proportion of businesses using AI has increased by 270 percent in the last couple of years.

Artificial Intelligence is changing how different business sectors operate, from customer service research on data to operations.
Artificial Intelligence is changing how different business sectors operate, from customer service research on data to operations.

The total AI investment made by businesses worldwide reached a record $77.5 billion by 2021, increasing the previous year’s $36 billion.

Screening and generating ideas for new products

A successful new product development (NPD) begins by finding good ideas for products and using proven guidelines to determine the best ideas to follow.

Follow these steps before you commit funds for the development of new products.

Idea generation

Create a list of customer requirements using the information from the sources listed below. It is important to look for the weaknesses in your products and the gaps in your product line, and areas of improvement for your product.

Brainstorm possible product issues

Join your team members to discuss problems with your product. Your service and sales staff communicate with your customers daily and receive feedback on your products and your customers’ requirements. Record the customer’s comments, product observations, and suggestions from your staff. Then, be sure to acknowledge their thoughts and encourage an open spirit of creativity.

Make use of your development and research (R&D) methods.

Utilize your company’s existing R&D procedures. Consider making modifications to your existing products or make adjustments to create new products following the feedback you receive from your customers and market.

Examine the quality control (QA) procedures

Find any flaws in your product and then identify possible solutions to address the quality issues.

Examine your customer complaint logs

Find the common weaknesses to your existing product range and then look for areas in which improvement is needed. Finally, find out more about how to handle complaints from customers.

Do your research

Check Your customers’ research, study your market, and make plans for further surveys of your customers and market if you find research areas. For example, what do your customers tell what they’re looking to find? What do they find annoying or inconvenient regarding your products? What do they find most challenging about using your products the most?

Discuss your business with your suppliers as well as other business partners.

Contact manufacturers, retailers, and sales representatives to gather their experience with your products and ideas on how to improve their products.

Learn about and research your competition

Try to learn about your competition. Look over your competitors’ product offerings and see the market’s response to their offerings. Do their products appear to be meeting the requirements which yours don’t?

Catalogs of study materials and information on products

You must be knowledgeable about the products that are available on your market.

Screening of ideas

If you have a list of possible new product concepts, you must decide which ones you want to pursue and which ones to remove. Think about your competitors and your products, their flaws, and the requirements of your target market. Consider the needs of your customer’s list that you’ve compiled, as well as the areas for improvement that you have identified for your product.

Set up standards to assess the ideas you have developed against. Your criteria might include:

  • the most frequently identified customer requirements
  • Improvements to the product are most desired.
  • the benefits for your target market
  • the technical viability of the concept
  • the extent and the amount of research and development that is required
  • The potential for profit from the idea. What would be its appeal for the marketplace? What is the best price you could offer it? What are the costs of making it available to the market in terms of total and per unit?
  • How the product is placed in the market. Do you see an opportunity? What is the distance to products from competitors?
  • the resources that it will require for development
  • The marketing potential of the concept
  • The fit to your company profile and your business goals.

SWOT analysis

The SWOT Analysis can assist you to determine what strengths as well as weaknesses in every concept.

Innovation support

Your inventive approach and ways to inspire innovation in your team will allow you to achieve your goals for your new product. Find out more about Innovation advice as well as grants and assistance.

Learn more about becoming an innovative company.

Also, think about…

  • Find out more about the events that promote the commercialisation of products.

Technology is always evolving. A significant portion of it can improve our lives by improving the way we learn or do our jobs in ways not thought of before. Machine learning and AI are at the forefront of the technology’s future, which includes their application of radar in technology. This article is to explain the terms AI as well as machine-learning are and how they connect to one another, and what their roles could be in radar technology.

What is Artificial Intelligence?

Simply stated, artificial intelligence is a technology which combines human brainpower with machines. This is achieved by the machine utilizing an array of algorithms for problem solving to accomplish tasks.

The origins of AI are in various disciplines of research, including futures, computer science and philosophy. AI research is split into streams that are related to AI application’s aim that is “thinking vs. acting” or “human-like decision vs. ideal, rational decision.” This makes use of four research currents:

  1. Cognitive Modeling is the ability to think like an human
  2. Turing Test – acting as an actual human when interfacing with humans
  3. Laws of Thought A weak AI can pretend to think. A strong AI is able to think.
  4. Rational Agent The intelligence generated through the action of agents that are defined by five characteristics which comprise:
    1. Operating independently
    2. Perception of their surroundings
    3. Persisting for a long time period
    4. Making adjustments to the changing environment
    5. Making and setting goals and

Artificial Intelligence agents can be classified into four distinct kinds:

  1. Reflex agent simple that responds to sensor data
  2. Reflex agent based on model that takes into account its internal condition
  3. Agent-based on goals that takes the most effective way to accomplish its goals using the logic of binary
  4. Agent-based on utility which’s function is to enhance its effectiveness

Each of the four agents could be a learning agent by the expansion of its programming.

What is Machine Learning?

The term “machine learning” is used to refer to techniques that can be utilized to tackle a range of real-world issues making use of computer systems that can solve problems by learning rather than programming to resolve issues.

Certain machines are able to operate without supervision. Other systems employ supervised learning methods that employ an algorithm based using a set of data points to gain insights into an unknown collection of data in order to build an understanding.

A third typeof reinforcement learning continuously learns by observing its surroundings. This information is acquired by interfacing with the environment via repetition.

The process of creating a machine-learning model generally involves three major steps:

  1. Model the process in which the modeler defines the issue then prepares and process the data set that is selected and selects the machine learning algorithm
  2. Estimation of performance in which the various parameters that define the algorithm are tested and the one that performs the best is selected.
  3. The deployment of the model to begin to solve the challenge on the unknown data

Machine learning mimics the human cognitive capabilities of beings, however in a separate manner.

How Do the Two Relate to One Another?

However, despite their distinct characteristics, There is some confusion as to the functions each technology performs. This is usually exacerbated due to the fact that both terms are frequently utilized to mean the same thing. In the real world, AI depends on machine learning to reach its goals.

So What is Link to Radar Technology?

Let us first define radar technology:

Technology known as Radar in its most effective form creates a 3D map composed of dots with different intensities and radial distances. They could be either static or move overtime at an acceleration v(t). Different sensors (Pulse, CW, FMCW, Doppler, etc.) are better at different aspects. A complete picture could require the use of several radars.

Synthetic aperture – When we use moving sources, we additionally receive the SAR effect, giving a more clear image as well as the 3D representation of every dot, much like 3D television, but with more quantitative data (camera imaging is qualitative). When we move dots, we also receive the SAR effect giving the same information as SAR.

The remainder is mostly post-processing like filters, Fast Fourier Transformation FTT and amplification. It also includes enhancements like Moving Target Detection MTD or MTI for moving target detection.

In reality, we could do more by using reasoning. We could also alter those parameters that make up the radar (e.g. frequencies or patterns of frequency elevation, amplification, directions of source, etc.) which allows us, for example, to more effectively adjust the parameters of the source for the target and to monitor it over time while tracking it.

AI in Radar Technology

We can use our “Rational Agent” which we have introduced in the previous context.

It operates autonomously (1) and be aware of the surroundings (2) and then adjust (the parameters of the radar) to adapt (3).

Artificial intelligence can provide an ability to make decisions with the aid of

  1. comparative external data (e.g., the cross-sections of a library of aircraft or dynamic movements of species of animals, a collection of biometric heartbeat patterns of terrorists who have fled).
  2. learned through the years and from the model application (machine learning)

In the area of perimeter surveillance the result of this logic could be:

Three people are advancing towards the border at GPS position x with a speed of y in the direction of Z. Human No 1 is carrying an item, possibly RPK74 type machine gun The other two aren’t armed. Human No 2 is the one with the heartbeat pattern of John Doe, the terrorist studied by John Doe. It is classified as a danger.

However, the rational agent also has another advantage which is the ability to design and attain objectives (4). Within an environment with the general goal for “perfect supervision of a perimeter” this could lead to the desired outcome: continuously suggest enhancements for the perimeter to allow for more effective monitoring.

AI used in radar part of a larger systemic AI design that is a part of a larger architecture. It may be

  • disjunctive offering the results of an application that is an intrusion detection system IDS , or the Radar Data Processing System RDPS;
  • orchestrated in which a Central Master AI unit assigns tasks other peripheral AI units
  • integrative in which interconnected AI Peripheries are connected with one giant Artificial Brain.

Where to Apply AI in Radar Technology

AI’s possibilities for AI for radar is infinite and could be used to create new applications and situations which we’re not in a position to imagine the possibilities of today (just as that the Internet could have done).

Let us look at some applications that are in use in the present.

  • Air Traffic Control – AI can help analyze and, in conjunction with intelligent RDPS, better manage an ever-changing airspace that is safer, more efficient and greener (with shorter air travel times as well as optimized itineraries, schedules and more);
  • Perimeter surveillance We already provided an example. The monitoring of government and military borders, as well as corporate perimeters , or even a private structure is expected to be improved significantly as well as being well reflected by the subsequent actions.
  • Medical devices such as radars could save lives. We can monitor heart, breath, perhaps detect cancer one day. The SkyRadar team has done lots of study on this topic and has a number of patents worth keeping. We’ll write more about this in future blog posts.
  • Manufacturing Monitoring production and safety monitoring or quality inspections are just a handful of the possible high-level goals that can be achieved.
  • Security for the homeland Ground-penetrating radars create an UAV that can spot and, in the context of an AI scenario, eliminate landmines, or moving radars are able to help in the fight against terrorists.
  • military – Based on the various scenarios discussed in the previous paragraph, the possibilities for the military uses that make use of AI using radar tech is numerous. That brings us to our next aspect…

What will happen to AI? AI will impact different areas of Technology!

Artificial Intelligence is a phrase that stimulates the minds of certain individuals, but evokes fear in the minds of others. It is true that AI is changing the way we live at an incredible rate. From driverless cars to specially robotics for specific purposes AI is intended to improve the quality of our lives.

Technologies that are powered through AI or Machine learning have already begun revolutionizing the world of work and bringing organizations huge benefits and adding tremendous value to their business.The industries of healthcare, transportation, logistics, finance , and industrial manufacturing, along with a myriad of others, will undergo massive changes due to the influence of AI and would develop to become more efficient as well as cost-effective and, most important, offer better services.

In all of its applications, I am the most impressed by the outcomes generated from AI within the areas of:

Healthcare

With the aid in the use of expert AI systems as well as robotic surgeons that are autonomous The risk involved with every type of surgical procedure can be greatly reduced, as even the smallest of operations can be carried out with incredible precision and efficacy.

Since AI systems continue to develop and learn overall, unlike humans who learn from their personal observations, these systems are likely to grow significantly better in diagnosing and treating ailments using the vast amounts of medical data available.

The research has proven how deep neural network can be trained to generate basic radiological results with high accuracy, through training based on archived millions of scans of patients that healthcare facilities collect. A number of giants have already made their debut in the field of healthcare robotics.

For instance, in 2000, Intuitive Surgical introduced the da Vinci system, which is a new technology that was initially advertised to help with minimally heart bypass surgery that is not invasive, it later gained considerable market share for treating prostate cancer. The company joined with its sole major rival, Computer Motion, in 2003.

The da Vinci, currently on its fourth generation offers 3D visualisation (as opposed to Monocular Laparoscopy) and wrist-worn instruments within an ergonomic device. Researchers are developing similar medical devices, and they are likely to boost and improve the average human life expectancy.

Care for yourself

We have chatbots as well as personal agents such as Google Home, Alexa, and Siri designed to assist us with simple questions.

We could be able to have robots with humanoids that help us with our daily chores. us. According to the National Bureau of Labor Statistics predicts that home health care aides will increase by 38% in the next 10 years [23.

This demonstrates the need for this market. Companies such as Amazon Robotics and Uber are developing humanoids to provide basic home help services.

Human-like Robot Sophia

The amazing advancements made in Natural Language Processing and Image processing made possible with Deep learning will help improve robots’ interactions with humans at home. Another area where AI can really help is the elderly care.

Although there are some devices on the market but a humanoid that is sustainable enough to assist the elderly is not yet in the works. AI is set to be an integral element of our lives, because our homes will be packed with advanced technologies, bringing higher efficiency and greater convenience, which will save us money, time, and energy. It will also provide our customers with superior services.

The most recent instance is Amazon Go stores which uses AI and Computer Vision to remove long lines of customers waiting to pay at departmental stores, thereby making it easier for us to save time and energy.

Autonomous Systems

No matter how sophisticated technology becomes, however, they cannot be considered to be a substitute for human existence.

In the course over time, each of the tasks that pose a threat to human life yet are essential are able to be completed by AI powered robots. This is a good example of fixing lines that are in danger, locating petroleum in deep ocean trenches, and being police officers against crime.

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