Flewup - A world-class robotics company

Flewup Technologies is a high-tech enterprises which specialized in research ,development and integration of service-oriented robots.Flewup Technologies founded by Mr.Aliriza Abdul Gafoor has built a well reputation for creating service robots Including renowned robot Roya, Indias first car showroom manager robot. Our mission is to develop service robots that enhance people’s quality of life. The team consists of expert engineers that design, craft and customize humanoid robots to help you to scale-up your organization to the best level.

  • Vision

    We focus on creating a better future by constantly focusing on creating innovative technologies that can really change the world.

  • Mission

    Our mission is to educate and inspire likeminded people all over the world to always strive for success no matter what their circumstances.

  • Values

    Integrity,honesty and passion for creating futuristic technologies are our core values and thats why we always Dream big, and focus on success.

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    Smart & Futuristic Technologies

    A dream doesn't become reality through magic; it takes sweat, determination and hard work and at flewup one of our dream was to pluck coconuts using smartphones and tablet computers.And finally flewro technology is the result of this dream

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    Artificial Intelligence

    Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

    AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple's Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.

    Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.

    While AI tools present a range of new functionality for businesses,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely.

    Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in general. Researchers and marketers hope the label augmented intelligence, which has a more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them.

    Types of artificial intelligence
    Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI systems that exist today to sentient systems, which do not yet exist. His categories are as follows:

    Type 1: Reactive machines. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to inform future ones. It analyzes possible moves -- its own and its opponent -- and chooses the most strategic move. Deep Blue and Google's AlphaGO were designed for narrow purposes and cannot easily be applied to another situation.
    Type 2: Limited memory. These AI systems can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way. Observations inform actions happening in the not-so-distant future, such as a car changing lanes. These observations are not stored permanently.
    Type 3: Theory of mind. This psychology term refers to the understanding that others have their own beliefs, desires and intentions that impact the decisions they make. This kind of AI does not yet exist.
    Type 4: Self-awareness. In this category, AI systems have a sense of self, have consciousness. Machines with self-awareness understand their current state and can use the information to infer what others are feeling. This type of AI does not yet exist.
    [Image: An explanation of the differences between AI and cognitive computing]   What's the difference between AI and cognitive computing?
    Examples of AI technology
    AI is incorporated into a variety of different types of technology. Here are seven examples.

    Automation: What makes a system or process function automatically. For example, robotic process automation (RPA) can be programmed to perform high-volume, repeatable tasks that humans normally performed. RPA is different from IT automation in that it can adapt to changing circumstances.
    Machine learning: The science of getting a computer to act without programming.Deep learning is a subset of machine learning that, in very simple terms, can be thought of as the automation of predictive analytics. There are three types of machine learning algorithms:
    Supervised learning: Data sets are labeled so that patterns can be detected and used to label new data sets
    Unsupervised learning: Data sets aren't labeled and are sorted according to similarities or differences
    Reinforcement learning: Data sets aren't labeled but, after performing an action or several actions, the AI system is given feedback
    Machine vision: The science of allowing computers to see. This technology captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis. Computer vision, which is focused on machine-based image processing, is often conflated with machine vision.
    Natural language processing (NLP): The processing of human -- and not computer -- language by a computer program. One of the older and best known examples of NLP is spam detection, which looks at the subject line and the text of an email and decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition.
    Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or by NASA to move large objects in space. Researchers are also using machine learning to build robots that can interact in social settings.
    Self-driving cars: These use a combination of computer vision, image recognition and deep learning to build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians.
    AI applications
    Artificial intelligence has made its way into a number of areas. Here are six examples.

    AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include chatbots, a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aid patients through the billing process, and virtual health assistants that provide basic medical feedback.
    AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. Automation of job positions has also become a talking point among academics and IT analysts.
    AI in education. AI can automate grading, giving educators more time. AI can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. AI could change where and how students learn, perhaps even replacing some teachers.
    AI in finance. AI in personal finance applications, such as Mint or Turbo Tax, is disrupting financial institutions. Applications such as these collect personal data and provide financial advice. Other programs, such as IBM Watson, have been applied to the process of buying a home. Today, software performs much of the trading on Wall Street.
    AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a more efficient use of time. Startups are also building question-and-answer computer assistants that can sift programmed-to-answer questions by examining the taxonomy and ontology associated with a database.
    AI in manufacturing. This is an area that has been at the forefront of incorporating robots into the workflow. Industrial robots used to perform single tasks and were separated from human workers, but as the technology advanced that changed.
    [Image: The impact of AI on marketing]   How AI affects marketing operations
    Security and ethical concerns
    The application of AI in the realm of self-driving cars raises security as well as ethical concerns. Cars can be hacked, and when an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing the programming to make an ethical decision about how to minimize damage.

    Another major concern is the potential for abuse of AI tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state.

    Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deepfakes, convincingly fabricated videos of public figures saying or doing things that never took place.

    [Image: How biased data leads to inaccurate AI predictions]   How data bias impacts AI outputs
    Regulation of AI technology
    Despite these potential risks, there are few regulations governing the use AI tools, and where laws do exist, the typically pertain to AI only indirectly. For example, federal Fair Lending regulations require financial institutions to explain credit decisions to potential customers, which limit the extent to which lenders can use deep learning algorithms, which by their nature are typically opaque. Europe's GDPR puts strict limits on how enterprises can use consumer data, which impedes the training and functionality of many consumer-facing AI applications.

    In 2016, the National Science and Technology Council issued a report examining the potential role governmental regulation might play in AI development, but it did not recommend specific legislation be considered. Since that time the issue has received little attention from lawmakers.

    Customer Service Robots

    Customer service robots are professional service robots intended to interact with customers. These robots come in humanoid and non-humanoid forms and automate much of the most basic of tasks in customer service. Like all robots, their value lies in labor savings, efficiency and uptime.
    The market for public relations robots is set for robust growth. In 2018, sales of public relations robots grew 53% over 2017, with an estimated 7,000 units sold, according to the International Federation of Robotics World Robotics 2018 Service Robots report. Between 2019 and 2021, approximately 40,500 units will be sold, representing a 37% compound annual growth rate (CAGR).
    Most customer service robots are used to assist customers in finding an item or completing a task. They’re being deployed in the retail industry to guide customers around a store, as well as in the hospitality industry. Customer service robots can be found in banks, shopping malls, family entertainment centers and more.
    The true value of customer service robots lies not only in their ability to interact with customers more cost-effectively than human staff, but their ability to collect customer data during face-to-face interactions. In this way, customer service robots have major potential for developing interactive marketing and re-branding strategies and for the tracking and analytics of customer behavior.
    Customer service robots can be deployed in a variety of ways. The market is expected to steadily rise as industry consolidation accelerates technological progress. As their ability to interact with customers and collect data improves, they’re expected to become an increasingly regular part of the customer service process.

    Welcome To The Robotics World


    As soon as we come across the word robot, we tend to imagine a metallic structure with arms and legs carrying a human-like appearance and running errands for our help. However, in actual terms, it’s just a machine operated externally or through a controller embedded within and doesn’t necessarily look like a human. Technically, robotics is a branch of Science and Engineering which deals with designing, constructing, and operating robots as well as computer systems for their control, sensory feedback, and information processing.

    Introduction to Robotics

    Interestingly, the concept is almost as old as the hills with the first robot dating back to 350 BC, built in the form of a mechanical bird, by a Greek mathematician named Archytas. Although the term was coined ages ago, the actual potential of the fully autonomous robotics was realised in the second half of the 20th century.

    APPLICATIONS OF ROBOTICS

    The primary objective of robotics was to just perform a set of complex tasks mainly in factories with parts of robots but now it has spread to a lot of fields. Today, we can find the following industrial applications of robotics -:

    Military: It goes without saying that military operations involve a high level of risk and hence it makes sense to use machines so as to save human lives. There a lot of varieties of military robots namely UAVs (Unmanned Aerial Vehicles aka drones), UGVs (Unmanned Ground Vehicles) and UUVs (Unmanned Underwater Vehicles). These are used to locate the terrorists and launching attacks. There are even four-legged robots for carrying heavy arms and ammunition.

    Education: Many schools and institutes are using robots to educate and engage the students for STEM programs (Science, Technology, Engineering, and Mathematics). There are a lot of kits available for students through which they can learn a lot about robotics. Not only this, but kids with autism and other behavioral disorders also find it more convenient to interact with robots and gain knowledge about various subjects.

    Healthcare: Various kinds of robots are being developed to be used in hospitals to aid the doctors and nurses in taking care of the patients. There are robots that can disinfect a place, take care of the needs of the patients and even remove unwanted elements from the body without surgery. There is also a robot named da Vinci which helps in performing surgeries with precision which are difficult to perform manually.

    Agriculture: Many small-sized robots are used in agricultural fields which are equipped with camera and sensors. These navigate through fields and detect the weeds and other kinds of infection. The sensors help in applying the spray only on the affected areas, thereby protecting the environment from the release of harmful chemicals in the air.

    Factory: Industrial robots are evidently being equipped on a large scale in factories building heavy equipment. Factors like negative population growth in certain countries, the disinterest of the younger workforce to indulge in factory work and time-saving efficiency of robotic parts are determining the surge in the usage of industrial robots. The most common illustration that can be cited here is the automobile factories that build cars through robotic parts along with human workers.

    Space: Several countries have built their own space robots carrying various shapes and sizes in order to explore the space. Some of them can’t even control their own weight on earth but work efficiently in space with excellent dexterity. Since there isn’t any gravity and certain situations are challenging for survival, these robots can be easily substituted in the space for capturing videos and for performing other routine tasks.

    TYPES OF ROBOTS
    From the heavy, metallic, and wired machines known as super robots to tiny devices known as nanobots, the field of robotics has been explored to a great extent. Enlisted below are the varieties of robots that have been designed lately. Let’s check out the list of some interesting forms of robots -:

    Exoskeletons: It’s a technology where an electronic body suit offers limb movement and increased strength to the user. Primarily, these are used for the military purpose to lift heavy load and for patients suffering from spinal injuries.

    Example: Ekso Bionics has developed full body ekso suits that can be worn by people who are victims of stroke or a spinal cord injury to get back on their feet. Originally developed for DARPA to be used by soldiers, these suits are also used in various rehabilitation clinics for patients with lower extremity weakness.

    Humanoid robots: These are the robots that have a body resembling with a human containing a head, two arms, a torso and two legs. A subcategory of humanoids is known as Androids who appear much like a human with respect to the aesthetic aspects and can imitate the expressions of a human.

    Example: Atlas is one of the most advanced humanoid robot developed by Google-owned Boston Dynamics. Although it’s not an android with human-like skin and expressions, yet it can do a lot of interesting stuff. It can walk in snow and re-balance itself just like us, open doors, lift boxes and even sense objects lying in front of it.

    Animal Robots: Bio-inspired robotics is a fairly new category of robotics where the natural biological characteristics of living beings are replicated in the form of animal-inspired robotic models. The traits of animals like the way they hop, climb, walk or crawl is observed and then efforts are made to iterate them in a machine setup.

    Example:  There is a robot named Cheetah developed by Boston Dynamics that can gallop at more than 29 miles per hour. A similar robot with the same name is developed by MIT which can sense obstacles and jump over them while running at 13 miles per hour.

    Rescue Robots: One of the most logical and sensible uses of robots is to deploy them in situations of disaster management for rescue operations. It takes a lot of courage as well as efforts to search and save the victims during a human or man-made disaster. Even though there have been instances when robots were designated for rescue operations but they failed to perform as per the expectations. It’s still considered as an emerging technology since there are a lot of challenges to be faced.

    Nanobots: These tiny devices are designed to perform repetitive tasks with precision at nanoscale dimensions of a few nanometers or less. These are applied in the assembly and maintenance of sophisticated systems or for building devices, machines, and circuits at the atomic or molecular level. Besides, nanobots are equipped in healthcare for the purpose of drug delivery, destroying cancer cells, etc.

    Example: A group of physicists at the University of Mainz in Germany have designed the world’s smallest engine from a single atom. It converts heat energy into the movement at the smallest scale that one has ever seen.
    Swarm: Swarm robotics is much like imitating a group of insects or ants in the form of tiny devices crawling together and forming certain designs. These can be used in the fields like agriculture, rescue tasks or military operations.

    Example: A swarm of 1,024 tiny robots was devised by Harvard University that could make certain formations like alphabets, five-pointed stars and other complex designs without any central intelligence.

    [Image: Amazing world of robotics-Swarm robots]

    Figure 5: Swarm Robots creating various formations DARPA Robotics Challenge
    DARPA Robotics Challenge i.e. DRC was conducted by US Defense Agency DARPA (Defense Advanced Research Projects Agency) which went on from 2012-15. The idea was to develop semi-autonomous robots that could help in rescue operations in a human-engineered environment. A lot of teams participated in the contest but only three of them were able to complete all the 8 tasks. The first price was bagged by Team KAIST with their robot DRC Hubo, followed by the runners-up IHMC and Tartan Rescue at second and third positions respectively.

    The tasks assigned to the robots include driving a vehicle, walk through uneven rubble, clear debris, turn valves, connect hoses, open doors, drill a hole and climb up the stairs. Though these are easy for humans, the same is extremely complicated for robots. It takes hundreds and thousands of lines of coding to make the robot take just one step. Besides, humans started walking after multiple years of evolution and even now when a child is born, it takes more than a year to be able to walk with perfection. So, there are still a lot of challenges and obstacles that have to be handled.

    CONCLUSION
    Today there are plenty of robots carrying a variety of shapes, sizes, and structures but all of them are subject to certain challenges. For instance, the robots participating in DARPA contest were efficient in human-like tasks but they didn’t have a proper system to perceive their environment and were simply following instructions from the operator. Then there are mini robots like Darwin developed by ROBOTIS who are quite skilled in walking, playing football, and even get up after falling but then they can’t be put to use in applications needing physical strength. There is also a robot named Cozmo by Anki which can even express feelings and play but it’s merely for entertainment.

    Moving on, there are certain implications of robotics that need to be discussed. It’s been a long-time notion that the development and deployment of robots are going to take away numerous jobs from the human workforce. However, Sherry Turkle who is a professor at MIT says that robots are not substitutes but companions of humans and their development would rather generate jobs.

    Another concern is that we need to set a limit on the nature of tasks that are designated to the robots. It’s logical to use them at places which are too dangerous for humans to access but it also raises a big question that if anything goes wrong, who will bear the blame. Undoubtedly, technology has always offered numerous benefits and plays an important role in our life but it’s equally important to decide the limit of its usage.

    Different Types Of Service Robots

    service robot is a robot which operates semi- or fully autonomously to performservices useful to the well-being of humans and equipment, they exclude manufacturing operations, and they are capable of making decisions and acting autonomously in real and unpredictable environments to accomplish determined tasks.