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Data home: what kind of data is generated by the ecosystem of smart things


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Utopian travelers predicted that the concept of a home as a place where you want to return again and again will disappear. The house will become a kind of long-term warehouse for storing things, while we will be anywhere in the world where there is Internet.

However, now, with the forced transition to quarantine, the house for many has become the only outlet, giving strength and relieving psychological stress. And for those who initially relied on home automation, the current difficult times are perceived as a kind of test for the strength of the concept of “digital fortress”.

A smart home is not just a space in which you can control curtains, a refrigerator, light bulbs, etc. A real smart home that uses IoT and the achievements of Data Science becomes a generator of valuable data that directly affects the quality of life and human behavior.

Today we talk about the impact of IoT data on the formation of habits and behavior patterns.

Data generators



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In 1999, technologist Kevin Ashton from the Auto-ID lab at MIT introduced the definition of “Internet of things”. And the first IoT device was a vending machine developed at MIT connected to the Internet. 20 years later, every second , 127 new IoT devices connect to the Internet .

According to Gartner, by 2022 a typical large single-family home could be equipped with more than 500 different smart devices connected to the Internet. In addition to the obvious automation of all routine processes, smart things will produce a huge amount of data that can be collected and analyzed.

In the reportSeagate Data Age 2025, released in conjunction with research firm International Data Corporation, predicts that by 2025, smart homes within global smart cities will generate up to 163 zetabytes of data.

On average, the number of human interactions with connected devices will be about 4.8 thousand times a day (one interaction every 18 seconds), regardless of where in the world they are.

Analysts suggest that by 2025, nearly 20% of the generated IoT data will be classified as “critical” for our daily lives, and about 10% as “supercritical”.

Systems based on artificial intelligence can quickly identify patterns and detect anomalies in data such as temperature, pressure, humidity, heart rate, air quality, vibration, and sounds.

There are many possibilities for using the information received. For example, when outdoor air quality sensors begin to transmit data to smart city systems, additional information will help monitor the environmental situation of large metropolitan areas.

Data house as a tool for earning



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Light bulbs, monitors, and other electronic devices can “adapt” to user activity: give advice on reducing energy consumption or automatically reduce energy costs, which will save money on utility bills.

An example of such a solution is the Spanish startup Smappee . The EnergyMonitor application allows you to understand which devices and how much consume electricity. You can connect not only energy consumers to the solution, but also its generators - windmills, solar panels, etc.

The system does not just turn off the light when there is no one in the room. The Smappee complex decides what to do with the flow of electricity - send it to a charging station for an electric car or create a reserve in long-term storage batteries in the basements of the house.

Another example is the Nest thermostat, which “learns” from the user's habits and automatically changes settings in just a few weeks, reducing the time for unnecessary use.

Such intellectual things provide information that can be used to minimize risks in property and life insurance.

Habits correction



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charismatic developer of the WolframAlpha scientific search engine, Stephen Wolfram, for the most part of his conscious life, structures all his information with the help of smart devices. He collects all kinds of data from medical sensors, environmental sensors and any other devices and systems with which he interacts, and can draw up a graph of the main parameters of his behavior over several decades.

In the case of medical data, any deviations from the “normal” (average) values ​​may indicate the onset of the disease. By the way, some biohackers measure hundreds of such indicators. So, Stanislav Skakun collectsdata on 780 biochemical and anthropometric biomarkers and 717 genetic traits. Some of the information comes from external sensors, including home ones.


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Chris Dancy - a man who "works on his own." Journalists call him "The most connected man on earth." At the beginning of his “career”, he used various wearable technologies, smart scales, tracker mattress pad, smartphone capabilities and much more - at different periods of his life from 300 to 700 data collection systems.

Initially, Chris simply wanted to improve his health, because by the age of 45 he was suffering from excess weight, did not control his diet, and smoked two packs of cigarettes a day. Having collected a huge amount of data on his behavior and well-being, a year later he got rid of bad habits and lost 45 kg.

Chris uses Gyroscope data aggregator, which collects statistics on Internet use, on entertainment, on physical activity and physiological condition (according to the readings of the heart rate monitor and other sensors), tracks the movement, records the use of different modes of transport, etc., and presents all the data in a clear and convenient form.

At home, all the data from Chris Dancy's devices has a direct impact on the environment, which automatically adapts to his mood and needs. “The house knows my behavior, ” he says . - If I worry about something and sleep poorly, then in the morning, after waking up, the room exposes a certain spectrum on the lamps, changes the temperature and turns on specially selected music. My whole life is determined by the information that I collect in real time. "

Dancy learned by heart the average figures that indicate the status of his well-being, due to which it takes much less time to analyze behavior patterns using smart objects.

Quarantine Health Indicators and Medicine



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With the help of the IoT-house, doctors will be able to remotely monitor the health of patients in real time - from a camera that provides temperature data in a non-contact, high-precision way, to remote patient monitoring systems (RPM, Remote Patient Monitoring).

RPM uses digital technology to collect health data and safely transmit the information to health care providers for assessment and recommendations. This type of service allows doctors to monitor the patient's condition after discharge from a medical institution, thereby reducing the number of re-hospitalizations.

Monitoring programs collect a wide range of health data: heart rate and variability, weight, blood pressure, blood sugar (for example, through the non-invasive FreeStyle Libre sensor), blood oxygen level (SpO2 saturation sensor), electrocardiogram (based on compact gadgets for cardiac analysis).

For older people, people with disabilities, as well as those who need palliative care, RPM will help you live at home, avoiding moving to specialized municipal centers and medical facilities. Connected to the smart home ecosystem, Remote Patient Monitoring can generally reduce hospital admissions, readmissions, and health costs.

Examples of such solutions include Biofourmis, which provides quick feedback services to quarantined patients. Using the Biovotion Everion wearable sensor, the company receives real-time information on 22 parameters - from the intensity of movement when walking to the speed of propagation of a pulse wave .

Homeowner as a Data Provider


Based on “home” data, insurance companies are able to offer low-premium services to consumers, banks may decide to change mortgage rates (or remind you to cut costs), and city services to lower utility bills. In the latter case, the i2O Water example is illustrative , which receives information about the water pressure from sensors built into water distribution systems. The company uses the information to accurately control the pressure in the water supply networks and warns customers about the need for maintenance.

If before the user was a simple consumer of smart services, now he has the opportunity to independently manage the data: collect it and sell it to service providers - city halls, Internet providers, security services, thereby forming a value proposition in the IoT-house services market. Ultimately, if the house is really smart, he will be able to earn and provide for himself.

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