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IoT

What does Internet of Things mean?

Internet of Things, commonly shorten as IoT, refers to Internet connection of devices (other than typical families of devices such as computers and smart-phones). Cars, kitchen appliances and even heart monitors can be connected through the IoT.
As the Internet of Things grows in the next few years, other devices will become part of this list.
 

What is an Internet of Things device?

Any standalone Internet-connected device that can be monitored and/or controlled from a remote location is considered an IoT device. Thanks to technological progress and the availability of increasingly smaller and more powerful devices, almost all products can be or become IoT devices.

What does Internet of Things Ecosystem mean?

All components enabling public and private companies and customers to connect to their IoT devices, including remote access, dashboards, secure virtual networks, gateway, data analysis and analytics, data archiving and security are part of the IoT Ecosystem.

What is an IoT gateway?

 

IoT gateways, like the IIoT gateway of ServerNet, support various critical functions, such as devices’ connectivity, connectivity to complex Resources and systems, protocols’ translation, data filtering and processing, security, update, upgrade, management and so on. Most powerful gateways, like ServerNet LS24, are also platforms for applications which process data becoming an intelligent part of a distributed system, defined as "edge computing".

What do Cloud Computing and Fog Computing or Edge Computing mean?

    Cloud Computing

Cloud Computing and IoT both help to improve efficiency in everyday activities, and between the two there is a complementary relationship. IoT produces huge quantities of data and Cloud Computing provides a route to make those data go towards their own destination.

    Fog o Edge Computing

Fog Computing is more than an intelligent name. Also known as Edge Computing, it provides a way to collect and process data on local computing devices instead of a Cloud or a Remote Data Center. Following this pattern, sensors or other connected devices send data to a nearby and local processing device, close to the edge of collected data. This could also be a device commonly called gateway, such as a common switch or a router, which processes and analyzes data.

 

IIoT

What does Industrial Internet of Things – IIoT mean?

An IIoT object actually is a recently developed IIoT device exclusively designed for its application in the fourth industrial revolution era.
IIoT objects’ aim is to optimize production processes through connection among machinery, to realize useful data for an analysis center, to have a preventing control on in use machines’ health and to control industrial production’s times. A company investing in new technologies can use both of them. But, the two are not synonymous. The Industrial Internet of Things is an evolution of IoT, which allows an intelligent device to have more contemporaneous connections and to work with a greater amount of data.

 

IIoT devices are stronger than IoT objects because they have to operate under extreme conditions. For example, they must withstand high temperatures, adverse weather conditions, corrosion and 24/7, 365 days a year operation. Moreover, IIoT objects are almost always applied to cranes, probes, industrial plants and other large machinery. It is difficult for workmen to reach and replace these devices and for this reason they are created to last long. As mentioned before, Industrial Internet of Things objects can work with a greater amount of data. This is because in a well-structured IIoT system, a device simply analyses incoming data to prepare them and to send them to a gateway such as the gateway of ServerNet. Moreover, IIoT objects, thanks to specific management apps, are deeply customizable for the company purchasing them. Finally, in terms of IT security, they have much more solid standards than IoT devices.
 

IoMT

What does Internet of Medical Things – IoMT mean?

The Internet of Medical Things is about to transform healthcare and, if it reaches its maximum potential, will radically change even every aspect of life of all people (physicians and patients) who, willing or not, are somehow involved.

 

Pen and paper have been the primary means of recording patient’s information for decades. But now health technology is changing in some important ways. Today, citizen services allow patients to plan their medical exams without the need to call a doctor's office and wait for a receptionist. Health IT allows physicians to take information with them wherever they go through apps on their smart-phones.
And this growing connectivity shows no sign of slowing down. Actually, it's just accelerating. Several research studies indicate such a growth rate that over 600 million IoMT devices could be reached in 2020 (by the end of 2015 this estimate was under 100 million). This number does not include wearable items such as trackers or computers for sports and fitness.
Briefly, a better connection to medical data from medical devices means more accessible data for medical professionals and a better healthcare for patients.
 

What are an EMR and an EHR and how do they connect to IoMT?

The biggest technological step forward in recent decades has probably been the growth in the use of electronic medical records, EHR (Electronic Health Records) and EMR (Electronic Medical Records).
The distinction between EMR and EHR is immediate, if you think of the term "medical" in comparison with "health". An EMR is a narrower view of a patient's medical history, while an EHR is a more comprehensive, generalized report of a patient's health.

In 2009, only 16% of hospitals in the United States used an EHR or an EMR, but this percentage rose up to around 80% in 2013, according to the Becker's Hospital Review. Previously, hospitals had several systems that handled with different functions, but EHRs unify them into a unique system.
 

How will IoMT transform healthcare?

Internet of Things is slowly beginning to enter the healthcare, both in hospitals and doctors’ offices, and in the homecare. In hospitals various medical machines, such as: ultrasound, thermometers, glucometers, electrocardiographs, anesthesia machines, laboratory machines, etc., thanks to the IoMT Ecosystem of ServerNet, connect and allow physicians, anesthesiologists and nurses to monitor patients’ health, not only with the help of IT systems dedicated to health services, but also through electronic devices.

This is immediately of great worth for a high and uniform quality of hospital’s service, for the mobility of the staff, but also for those situations requiring in-depth study by doctors, who without the historical data could not have a full view of medical history.
Imminent implementation of Artificial Intelligence, starting from training and learning phases (machine learning), requires a more accurate and high-definition acquisition and analysis of data compared to what is needed, in terms of quality and quantity, for the filling of a medical record as a history of clinical progress.
This makes the previous data acquisition system, if present, obsolete as it is partial due to the absence of videos and the lack of "waveforms".
 

How will IoMT transform patient’s homecare?

Unfortunately, some patients do not take their medicines in the appropriate doses or at the right time.
Home installed smart medicines dispensers could automatically send information to the Cloud and alert physicians if patients do not take their medicines. More generally, this kind of technology could allow physicians to be aware of any potentially dangerous behavior patients may have.
This technology allows patients to have a more active role in their own health care.
A portal allows users to access the healthcare provider's website to view their own medical records, download forms and prepare for medical exams.
Finally, home monitoring systems allow patients and physicians to keep track of an individual's health even when he/she is not in a doctor's office and to avoid unnecessary travels and expensive medical exams.
 

Big Data

What do Big Data and Analytics mean?

Big Data is exactly what it seems: a great amount of data.
Internet of Things allows generating more data than ever before, and these amazing numbers are still rising. According to Cisco, the Internet of Everything, which consists in all people and things connected to the Internet, will generate 507,5 zettabyte of data by 2019. To make a clarification, a zettabyte corresponds to a trillion gigabyte.
Many experts in the branch and ServerNet first and foremost, believe Fog Computing will be instrumental in the analysis of all these data, because it is offers advantages which are not available in a Cloud Computing-based model. All this involves a faster analysis and a reduction of costs, which is above all due to a significant reduction in data transmission and to a simplification of archiving and managing processes with the benefit of greater reliability of the net and applications.
 

Artificial Intelligence

What does Artificial Intelligence mean?

Simplifying, we could define artificial intelligence as the ability of a technological system in solving problems or performing tasks and activities typical of Human mind and ability.
Talking about IT, we could identify AI - Artificial Intelligence as the discipline dealing with making machines (hardware and software) able to "act" autonomously (solve problems, perform actions, etc.). Characteristic of Artificial Intelligence from a technological and methodological point of view is the learning model through which intelligence becomes skilled in a task or an action. These learning models are what makes the difference between Machine Learning and Deep Learning.
 

How does Artificial Intelligence work?

AI functioning mainly consists of four different functional levels:

    • comprehension: through simulation of cognitive capacity of data and events correlation, AI (Artificial Intelligence) is able to recognize texts, images, tables, videos, voice and extract information, or thanks to a suitable middleware, such as the middleware of ServerNet, find this information already structured.

    • reasoning: through logic, systems are able to link the multiple information collected (through precise mathematical algorithms and in an automated way), or always thanks to the specific middleware, find already related data.

    • learning: what we are talking about in this case are systems with specific functionalities for the analysis of data inputs and for their "correct" restitution in output (this is the classic example of Machine Learning systems that, with automatic learning techniques, lead AI to learn and perform various functions).

    • Human Machine Interaction: what we are referring to in this case is the way in which AI works in relation to its interaction with human beings; it is here that NLP - Natural Language Processing - systems are strongly advancing; these are technologies that allow people to interact with machines (and vice versa) exploiting natural language.

 

Again, middleware is the one facilitating the interaction between AI and its user, enhancing data with metadata for the comprehension and reasoning phases; in fact, it solves 3 out of 4 of any Artificial Intelligence implementation, leaving the learning phase (machine learning) to the specific field’s experts and academics.
 

What does Machine Learning mean?

What we mean by Machine Learning is automatic learning, understood as the ability of machines (computers) to learn without having been explicitly and preventively programmed.

Machine Learning allows computers to learn from experience; learning is present when program’s performances improve after the performance of a task or the completion of an action even if wrong, starting from the assumption of "learning by making mistakes", which also applies to Human Beings.


Talking about Machine Learning from an IT perspective, we can say that instead of writing the programming code through which, step by step, we "tell" the machine what to do, the computer is provided with data sets entered into a generic algorithm, which develops its own logic to perform the required function, activity or task.
 

Middleware

What is a Middleware?

In 2000, during a workshop having as a result a 30 pages RFC (RFC2768), many people tried to define what a middleware is.

They were not able to do it, because a middleware is everything staying in the middle between two systems, two elements of a system or an object connected to another one.


ServerNet offers a middleware between medical and industrial machines and their user systems, keeping on evolving like machines and all systems using them do.

Actually, an obsolete middleware collecting data from a medical machine to keep it in a medical record is completely different from a middleware asked to collect data, waveforms, images and videos for their use with the implementation of Artificial Intelligence.