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Machine Learning

Machine Learning is a branch of Artificial Intelligence that teaches machines to learn and improve automatically, through observation of data, direct experience or instructions.

ML works through accurate models transmitted with a training process. Machines learn by memorizing and recognizing these models (for example, the difference between a cat and a dog), acquiring the capacity to answer questions.

Quality and quantity of the data collected are the most important factors to determine the accuracy of the models taught to the machines.

Because ML can be applied to any sector, it is used by many industries, for different purposes. Its applications range from the financial services to government, from healthcare to retail, from transportation to fuel industry.

Internet of Things

The Internet of Things is a system allowing objects equipped with sensors to exchange data over the Internet, but also with other smart objects, creating an interconnected environment controlled by a platform.

Remote control and monitoring of objects are cost and time-saving, plus they bring freedom of movement and peace of mind. IoT enables simple smartphones to take control of all appliances in your home, the front door and the heating system. And these are just a few of the applications of the IoT in smart homes.

Car and bike sharing, smart parking lots, smart traffic and street lights, real-time information on maps, virtual shops, are only a few of the incredible improvement of our everyday life in smart cities.

IoT can be applied to virtually any objects, boosting the efficiency of services and improving our quality of life, from medical facilities to transportation, from domotics to leisure.

Artificial Intelligence

AI is a form of intelligence manifested by machines, as opposed to living beings’ intelligence. John McCarthy, who coined the term in 1956, defined it as “the science and engineering of making intelligent machines.”

AI aims at creating machines reacting like humans. To reach such an achievement, it must include features such as speech recognition, learning, planning and problem solving. Nowadays, AI is essential to technology industry.
However, AI implies big programming challenges such as:

• Knowledge
• Reasoning
• Problem solving
• Perception
• Learning
• Planning
• Ability to manipulate and move objects

In order to make it possible for machines to behave like humans, it is necessary to feed them with huge amounts of information, because they literally need to learn how to behave. Getting to integrate logic, thinking and problem-solving in machines is something extremely difficult to accomplish.

Virtual Reality

Virtual Reality stimulates senses to make the brain believe the existence of something that is not physically present. If senses experience enough immersion, the illusion is successful. Mental and physical immersion enables users to reach a deep mental involvement making them believe that the virtual environment is real.

The more senses are stimulated, the better the experience. To achieve senses activation, it is necessary to use special equipment such as head mounted displays (HMD), special gloves and accessories, etc.

Interactivity is another key element for effective VR. It is fundamental that the virtual environment responds in a timely and natural manner to the activities of the users, to maintain a total and surrounding illusion. If this does not happen, the human brain is quick enough to notice it and the sense of immersion might vanish.

Cloud Computing

CC is the system through which you can store data and applications on remote servers, and accessing them via the Internet, rather than saving or installing them on your PC. It allows great flexibility, making possible cost-effective choices in terms of resources management.

Flexibility means working from anywhere at any time, because information stored in the cloud is always available (e.g. email account storage). It also means paying only for what you use, because you no longer need to invest in expensive hardware for data storage and process.

There are three types of CC:

• Infrastructure as a Service (IaaS), a third party provides the infrastructure for the data center: servers, storage and networking hardware, etc.
• Software as a Service (SaaS), applications are hosted by a third party provider which makes them available over the Internet.
• Platform as a Service (PaaS), a third party provider delivers hardware and software tools over the Internet.

The main benefits of a CC system are:

• Adaptability, because CC allows customization while granting control over the code.
• Multitenancy, because applications can be provided to different customers and tenants.
• Reliability, because CC is hosted by a third party.
• Scalability, because thanks to the IoT, CC makes software function with different devices and applications.
• Security, because there are more resources for data security and centralization.

Data Mining

Data Mining is a system used to transform raw data into useful information, thanks to specific software. It is typically employed for marketing strategies. For example, supermarkets use loyalty cards to draw information about customers’ habits and preferences collecting data on purchases.

Data mining is at the bottom of machine learning models and artificial intelligence.
Effective data mining relies on adequate data warehousing and efficient analysis carried out by IT professionals and can bring many benefits such as automated decision-making, accurate prediction and forecasting, cost reduction and customer insights.

Predictive Analytics

Predictive analytics needs a series of statistical techniques to make predictions about future events, like trends and behavior patterns. Statistical techniques include data modeling, machine learning, Artificial Intelligence, deep learning algorithms and data mining.
Predictive analytics can be used for virtually any field. Some of them are actuarial science, marketing, financial services, insurance, telecommunications, retail, travel, mobility, healthcare, child protection, pharmaceuticals, capacity planning, and social networking.

As for Agriculture, cultivable land will be ever-decreasing while population will constantly grow, causing huge challenges to address. Predictive analytics is here to help to make the most of cultivable land, avoiding waste of water and fertilizer and optimizing yields.

In Construction, materials represent an important expense. Being able to predict the quantity of materials and personnel necessary on site can make a huge difference when it comes to budget forecast. Predictive analytics can also help in forecasting busiest times of the year, based on seasons’ changes. Usually, cold seasons are the less busy for constructions, due to adverse weather conditions. Budget can then be distributed more equally during the year, once predictions are made.

Augmented Reality

AR is an interactive, artificial environment generated by a computer that superimposes on the real environment, offering multisensory experiences.

The effect produced by the computer can be either constructive (when elements are added to the natural environment) or destructive (when some elements of the natural environment are masked) and it is so perfectly mixed with the physical world that the immersive experience becomes absolute.

There are 4 types of AR:

• Marker-based AR requires visual object and a camera to scan it. It can be a QR code or a sign. The markers provide users with images and animations.
• Marker-less AR is position-based. Its uses GPS, a compass, a gyroscope and an accelerometer, to provide info based on the user position and movements. They can be maps and directions with info on the businesses and interest points in the area.
• Projection-based AR allows to project a hologram on physical, raw objects, to simulate the possible aspect they might acquire with different patterns and colors, avoiding to physically modify it before.
• Superposition-base AR uses real, physical environment to superpose on it virtual objects to simulate how they would fit. This type of AR is largely used by furniture manufacturers to help customers getting the idea of what they would look like in their homes.

AR requires the use of specific devices, like smartphones, smart glasses, HUD (head up display) or VRD (virtual retinal displays) to be possible.

Applications of AR are endless and vary from gaming to medicine, from education to military.