IOT / Big Data / Digital Immortality

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This page discusses the Internet of Things (IoT), Big Data, and Digital Immortality.

The Internet of Things

Internet of Things

The Internet of Things refers to the devices around the world that collect and share data amongst themselves and are connected via the Internet. In essence, the goal of IoT is to increase the shareability of data among people and devices. To function properly, an IoT system requires transmitting, receiving, and evaluating data in a feedback loop. Nearly any device that can be assigned an Internet Protocol (IP) address can contribute to the Internet of Things. [1]

The applications brought about by IoT have become virtually limitless. For example, by setting up a smart tag on a room door, at the tap of a phone, numerous applications can be turned on, from the lights to the TV to the speakers. Although these devices can execute a series of automated commands, they require a central intelligence system allowing the data to be shared and commanded through one device, typically through a HomePod or Google Home.

The History

The idea of transferring data to maximize efficiency is something that humanity strives to achieve. However, the concept of using physical objects to share data via the Internet was not something that had been done until the 1980s when students at a university decided to modify Coca-Cola vending machines to track the inventory remotely. [2] This was just the beginning as the term “the Internet of Things” was created in 1999 by the computer scientist Kevin Ashton while working at Procter & Gamble. Ashton originally proposed the idea of including RFID chips in products in order to track the inventory as it moved through the supply chain. [3] In the late 90s, the web was a new technology on the rise, and it was stated that Ashton used the word “Internet” in IoT as a way to generate excitement from executives about the project. Due to the growth of the web and the need for data to be more readily available, IoT was quickly adopted by companies. By the 2000s, a company known as LG released its first smart refrigerator. [4] When Samsung first released a similar fridge, they did not see success. Many consumers saw it as expensive and unnecessary, but smart fridges proved to become a booming new technology with their ability to transfer data across devices. The next phase of IoT came about through the development of smartphones. In the mid-2000s, telephone companies began to create phones that could serve as portable laptops, allowing people to access the Internet wirelessly through their phones. After the adoption of smartphones, IoT grew at an alarming rate, with practically all devices now holding the capability to transfer data. [5]

Applications of IOT

The application of the Internet of Things spans across all sectors of life. From homes to infrastructure to medicine to businesses, IoT has positively affected people’s lives.

IoT in Home Automation

IoT in Home Automation

As home automation has become more and more prevalent, a good example of IoT can be seen in its application in homes. Smart homes have become increasingly popular in today's society, with over 43 million devices being used in the U.S. in 2020. [6] By 2025, it is estimated that 20% of the world’s households will own smart home technology. [7] Through home automation, consumers have the ability to customize their homes to their liking and the freedom to operate their home appliances through their phones or virtual assistant technology. With technological advances in IoT, releases of various products have allowed consumers to create customizable automation in their homes.

For example, Amazon released a weight pad to be placed under one’s mattress and measures changes in weight. Connected to an Alexa, when users get up in the morning, the weight pad will detect a weight shift and execute a series of commands to assist users with their morning routine. When individuals get up from their bed, the automation begins. Window blinds open themselves, music plays around the house, and morning coffee brews in the coffee machine. [8]

Another example of home automation is virtual house keys. Using smart locks such as August, individuals are able to connect them to their phones to automatically unlock their door when they are within close proximity. Such technology eliminates the need to carry keys around and enables users to share virtual keys to close friends and family as well. [9]

IoT in Transportation

IoT in Transportation

On a broader scale, IoT can be applied to areas such as transportation networks or "smart cities," thereby reducing energy consumption and improving overall efficiency; this helps individuals to better understand and improve the way in which people live and work. For instance, individuals are able to plan out their transportation routes from the fingertips of their phones. This capability is due to the fact that trackers have been enabled on transit systems, allowing individuals to be kept up-to-date with bus times in real-time. [10]

IoT in Medicine

IoT in Medicine

Through the aid of the Internet of Things, health professionals are now able to reach individuals beyond the clinic. When a patient is not at the doctor’s office, home monitoring devices allow doctors to monitor and analyze their patient’s health. This method of delivery of healthcare is known as remote patient management/monitoring (RPM). Throughout COVID-19, this became a popular method of providing healthcare to patients. [11] Video chats became a new normal in contacting and helping patients without putting patients and practitioners at risk.

A good example of RPM devices is heartbeat sensors. Currently, the sensors are able to transmit the data to the patient’s smart devices, allowing patients to gain further insight into the current condition of their hearts. [12] This enables patients to take preventative actions as they can visually see if there is something wrong. Before such developments, patients would need to wait for the data to be processed after testing and return to the doctor’s office once the information became available.

Another common RMP device is a glucose monitoring device. Previously, individuals would need to go in and do a test at the doctor’s office to check their glucose levels. With new innovations to RMP devices through advances to IoT, millions of individuals are able to better track their glucose levels and overall health by accessing the data in real-time and acting accordingly. [13] [14]

IoT in Business

IoT in Business

In recent years, the use of IoT in a business place has been the driving force behind several applications. Enterprise resource planning (ERP) works exclusively around the concept of sharing data amongst devices to allow more shareability and inclusion of information.

With respect to operations, logistics, and supply chain management, something as small as shipping a singular product would involve several devices and mediums that would collect the data on that shipment and make it available to the company, delivery drivers, and customers.

From a marketing perspective, the use of IoT has allowed targeted ads to be commonly adopted by large companies. If companies are able to track consumer data from any of their various devices, it will allow them to gather data to understand what consumer needs and trends are. In turn, the analytics captured from devices will allow companies to find the best and most proactive way to make strategic advertisements and ultimately meet customers' needs and wants.

It is stated that IoT also facilitates the continuous optimization of business processes and even impacts employee engagement and performance, serving to improve businesses and making the inner processes more efficient with the use of data and greater insights. [15] IoT enables organizations to enhance their productivity, services, and procedures while also better serving their clients and managing their workforces. IoT is the backbone of all industries and will only become increasingly more prevalent as technology advances. [16]

The Connection Between IoT and Big Data

Big data plays a large role in collecting and storing the data that is provided by IoT. IoT allows for the gathering of data to occur amongst all smart devices, which can then be transferred via the Internet and assorted and analyzed for big data. It is said that in several studies, the use of IoT is expected to generate 4.4 trillion gigabytes of data in 2020 [17], and this figure is likely to increase as IoT becomes more common in households in the form of smart devices and smart appliances. [18]

The Future of IoT

It is evident that the range of IoT spreads across all aspects of life, and this technology is only going to continue to grow in the future.

One of the primary ways that IoT will grow is through the sheer amount of smart devices that will be produced. Within the next 20 years, it will be highly likely to see most, if not all, home appliances being able to communicate with one another. Another thing that will assist the growth of IoT is the improvement of the Internet and the speed at which data travels. With the 5G Internet becoming popularized, internet speeds have already improved drastically.

As technology continues to improve, IoT will too, and the effects of this are already prevalent through our devices. It affects our homes, workplaces, hospitals, schools, and roads and has become an essential part of digitized information.

Two Types of Data


Anything that can be recorded or saved is known as data. Data are facts, figures, observations, or recordings that can take the form of images, sound, text or physical measurements such as distance, weight, or wavelengths. [19]


Data itself has existed for thousands of years, beginning with ancient civilizations that recorded numbers, facts, or figures for their everyday life. Overtime, data grew in volume and variety, and the methods to record them also became more modernized. This led to the birth of Big Data, and below are the most significant events in the development of Big Data. [20]

1926 – Nikola Tesla predicted that humans will be able to go wireless and stay connected using a pocket-size device, which is the smartphone. Nowadays, smartphones are so powerful that they are capable of generating and processing a huge volume of data. [21]

2001 – Doug Laney, an analyst with the Meta Group, publishes a research paper about the Volume, Velocity, and Variety of data. A decade later, the “3 V's” have become the generally-accepted three defining dimensions of big data, although the term itself does not appear in Laney’s note.

2005 – Hadoop was invented as an open source solution for storing and processing large unstructured datasets.

2008 – 9.57 trillion gigabytes of data has been processed by the world’s CPUs. Google processed 20 petabytes of data in a single day.

2012 – There are 500,000+ data centres across the world which can occupy the space of 5,955 football fields.

2015 – Google is the largest big data company in the world that stores 10 billion gigabytes of data and processes approximately 3.5 billion requests every day.

2015 – Amazon is the company with the most number of servers—the 1,000,000,000 gigabytes of big data produced by Amazon from its 152 million customers is stored on more than 1,400,000 servers in various data centres.

Big Data

Big data is defined as the gigantic amount and variety of data that is being collected daily. This is the data that is so large, fast or complex that it is difficult or impossible to process using traditional methods. The data are analyzed to help achieve goals such as increasing the speed at which products reach the market, reducing the amount of time and resources required to gain market adoption, targeting various audiences and demographics, and ensuring that customers remain satisfied [22]

The V’s of Big Data

In the first definition of Big Data, Doug Laney described it using three V’s: Volume, Velocity, and Variety. Overtime, as Big Data gained more recognition and garnered greater investments, more V’s were also added to the definitions. [23]

Volume: How much data is received. Organizations collect data from a variety of sources, including transactions, smart (IoT) devices, industrial equipment, videos, images, audio, social media and more.

Velocity: How fast is data received.

Variety: The type of data received. With the rise of big data, data comes in new unstructured data types. Unstructured and semistructured data types, such as text, audio, and video, require additional preprocessing to derive meaning and support metadata.

Veracity: The accuracy or truth of the data.

Value: The value that the data can bring to the business.

Google's BigQuery

From Google’s BigQuery, the services that it offers are: [24]


Built-in machine learning: BigQuery ML enables data scientists and data analysts to build and operationalize ML models on planet-scale structured, semi-structured, and now unstructured data directly inside BigQuery, using simple SQL—in a fraction of the time.

Analyze and share data across clouds: BigQuery Omni is a fully managed, multicloud analytics solution that allows individuals to cost-effectively and securely analyze data across clouds, including AWS and Azure, and share results from a single pane of glass across datasets.

Real-time analytics with built-in query acceleration: BigQuery has built-in streaming capabilities that automatically ingest streaming data and make it immediately available to query, along with native integrations to Google Cloud's streaming products like Dataflow.

Unify, manage and govern all types of data: Use BigLake to explore and unify different data types and build advanced models.

Geospatial analysis with BigQuery: BigQuery can augment your analytics workflows with location intelligence.

Amazon Web Services

Amazon Web Services

Amazon Web Services (AWS) is a similar service to Google’s BigQuery. A few services that stand out are: [25]

Analysis on Data movement: Combine, replicate, and move data across different sources.

Data lakes: Refers to how Big Data is stored. A data lake is a centralized place that can store both structured and unstructured data. [26]

Log analytics: Analyzing the logs or machine-generate data for operational insights [27]

Streaming analytics: Analyzing data continuously instead of in batches

Business intelligence: Provide business insights from the provided data.

Netflix Analytics

Netflix Analytics

Unlike Google’s BigQuery and AWS, Netflix Analytics is used internally to create recommendations for customers and evaluate potential projects. [28]

The most basic data are information such as subscribers' demographics, shows liked, categories browsed, or titles searched. Netflix also collects information on user interactions with presented content, such as the date and time a user watched a show, which device was used, whether the show was paused, resumed after pausing, and finished, and the time it took for a user to watch the show.

From the data gathered, Netflix was able to improve users’ experience by recommending shows that are relevant to them. Furthermore, the data can be used to evaluate the potential profitability of a new project.


Increase efficiency and cut costs: An organization can identify elements in the business process that are hindering efficiency. Removing invaluable and unnecessary steps in a business process will help an organization cut costs.

Improve the hiring process: By hiring the right person, a business is more likely to move in a positive direction in the future. From implementing big data, a software system can scan resumes and LinkedIn accounts for keywords that match a company’s job description. This will allow companies to find the most optimal candidates for a particular job.

Improve customer service: Big data provides a window into consumer buying habits allowing an organization to play into people’s preferences and provide desired products or services. This will help an organization to retain current customers and earn new ones.


Lack of Expertise: It is hard to obtain big data experts, is costly, and takes a great amount of time to get the specific skills.

Quality of the data: Data scientists need to check whether the data is correct and ensure that the data is in an appropriate form that can be processed. This quality check may slow down the analyzing speed. An example is with Netflix’s user profile. If two users share the same profile in an account, then the data gathered for that specific profile may not be accurate.

Ethical Concerns

Privacy and Informed Consent: Is the person allowing their data to be collected? Do they even know if their data is being collected?

Lack of transparency: Big tech companies such as Google and Facebook are gathering an enormous amount of data everyday. However, there is a lack of transparency with what the data are being used for and what data are being collected.

Facebook and Cambridge Analytics: [29] Facebook collected and sold the data of over 70 million people in the U.S, and the data were used to influence the US election. This is a famous example of the lack of transparency from big tech companies, specifically with Facebook. In this scandal, it was discovered that Facebook sold the data of more than 80 million. The data was then used to influence the 2016 U.S. presidential election.

The Future of Big Data

Machine Learning: [30] Big Data is currently being used to train machine learning and AI.

Due to its nature of having both unstructured and structured data, machine learning and AI can develop themselves through processing these data.

Big data analytics is also becoming more accessible through Google’s BigQuery and Amazon Web Services.

Lastly, big data can be applied to trending and upcoming technology such as digital immortality. In theory, the IoT devices can record the characteristics of a person (the way they talk, their voice, their behaviours, etc.), turn them into data, and create a digital profile of a person.

Digital Immortality


Digital immortality is the notion that the characteristics and qualities of an individual are uploaded and saved onto a digital space such as a computer, virtual human, or digital avatar. [31] Digital immortality exists in two forms: one-way immorality and two-way immortality.

One-Way Immortality

This type of immortality exists in a passive or static mode. The deceased continues to display an online presence after death, but individuals are only able to access the information in a “read-only” format. An example of one-way immortality is a static Facebook memorial page dedicated to a deceased individual. [32]

Two-Way Immortality

This type of immortality is active; it relies on a digital footprint left behind by a deceased individual to create interactive digital personas. These digital entities “impersonate the dead” and interact with the user through various modes of communication, such as text, video, or voice conversations. Chatbots are an example of two-way immortality. [33]


Where We Are Today

With respect to digital immortality today, individuals and companies have created a variety of applications that allow users to leave a digital footprint or legacy.



Launched by Eugenia Kudya in 2017, Replika is an artificial intelligence (AI) chatbot that provides companionship to individuals by interacting with them on a one-on-one basis. Individuals are free to express their thoughts, feelings, and experiences with the AI persona, and the more an individual interacts with it, the more intelligent it becomes. Created from a sophisticated and complex system, it effectively processes data, thereby allowing the AI companion to learn and mimic an individual based on their responses. In essence, Replika becomes the individual it is communicating with—you! [34]

HereAfter AI


MyWishes is an application created by James Norris in 2019 and allows individuals to plan for their physical and digital data ranging from uploading messages to drafting wills and testaments to planning for funeral wishes. Individuals are able to create a digital legacy to leave behind by documenting “goodbye” messages to be published by a trusted contact on predetermined dates and times in the future. To ensure that their digital footprint is secure, individuals are able to complete a digital will with instructions on what should happen to their online accounts upon death. With respect to funeral wishes, individuals are able to plan how they would like their ceremony, including messages to be read and curated playlists to be played at the funeral. [35]

HereAfter AI

Founded in 2019 by James Vlahos, HereAfter AI is an interactive memory app that enables individuals to upload aspects of their lives to a digital space. Friends and family are then able to communicate with their digital avatar both during the present and when they pass away. Before they pass away, individuals may audio record answers to questions prompted by a virtual interviewer or have the freedom to share their own stories. Individuals may also upload photos to the app. [36]


Leaving a digital legacy today requires individuals to actively use the Internet, social media, and various other applications. In order to upload 100% of our mind and consciousness, it requires more than curating goodbye messages and audio recording a series of stories to be published at a later date.

The basic steps to uploading the mind into a digital eternity are to: [37]

1. Retrieve information from an individual’s brain

2. Recreate the brain artificially

3. Emulate the artificial brain digitally

However, there are two primary challenges concerning uploading our minds to fully achieve digital immorality, specifically scientific hurdles and technological capabilities.

Scientific Challenges

Scientists today still lack a solid understanding of the brain due to its complexity. As the human brain is comprised of 86 billion neurons and 100 trillion synapses, scientists would need to create a comprehensive map of the brain, known as a connectome, in order to illustrate the neural connections. The difficulty in this stems from the fact that the connections between neurons and synapses have different functions, and scientists do not fully comprehend neural signalling. [38] Furthermore, scientists would need to extract the information stored within the brain through technological procedures, and doing so with today’s technology is not feasible.

Technological Challenges

Once an individual’s neural activity is mapped out, a computer architecture is used to run lines of code to reconstruct the brain and, ultimately, allow for digitization. However, the issue with this is that a computer today does not have the processing power and capability to store the immense amount of information stored in the brain. The human brain is estimated to have a memory storage capacity of 2.5 petabytes, whereas a computer’s is only a fraction of that. [39]

Only when steps 1 and 2 are successful would our minds have the opportunity to be uploaded into a digital eternity.

Ethical Implications

The concept of digital immortality is not without ethical implications. It affects the deceased, the living, as well as animals.

The Deceased

Currently, an individual’s digital persona is curated from the information they left behind, such as the Facebook posts they uploaded, the Instagram stories they shared, or the voice memos they recorded on HereAfter AI. Without regard for an individual’s offline presence, digital immortality as we know it today fails to capture a complete picture of an individual’s character; the digital legacy left behind may only tell a fraction of who the individual was as a person. In turn, this may affect the integrity and accuracy of the deceased’s memory. As technology has advanced, individuals have lost control over their data, information, and privacy. From search histories to one-on-one online conversations to FaceTime video calls, these unintentional traces of records of information that an individual did not consent to may also be revealed. [40]

The Living

Over the years, there have been numerous applications created by for-profit companies that allow users to either leave a digital legacy or interact with a digital persona. Individuals using these applications are required to pay for such services, thereby allowing corporations to capitalize off of both the living and the deceased. Aside from the profits that these companies earn, it leads to concerns with respect to the grieving process. Rather than letting go, individuals may find themselves attached to these digital profiles and rely on them as coping mechanisms.

Another difficult aspect to consider is ownership. Who has ownership over the digital entity once an individual passes away—is it the virtual persona, someone dear to the deceased, or the corporation who created it? [41]


In order to safely extract information and digitize it, neuroscientists would need to experiment on animals before testing such methods on humans. This raises an abundance of questions, stemming from which species of animals should be tested, what testing methods should be used on the animals, and how to experiment on the animals in a manner that is humane. [42]

The Future of Digital Immortality

The 2045 Initiative

The future of digital immortality has some uncertainties due to the scientific and technological complexities that we would need to overcome. However, an individual by the name of Dmitry Itskow started the 2045 initiative, stating that by 2045, there will be a hologram-like avatar of individuals.

In four phases, Itskow believes that: [43]

Avatar A (2015-2020): A robotic version of a human body is controlled remotely through brain-computer interfaces (BCI)

Avatar B (2020-2025): An individual’s brain is transplanted into an avatar upon death

Avatar C (2030-2035): An individual’s personality is transplanted into an avatar with an artificial brain upon death

Avatar D (2040-2045): An individual is developed as a holographic-like avatar

Will we be able to achieve this by 2045? Only time will tell.


Alex Silva Duy Nguyen Jessica Wong
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada


  40. 10.1007/s12124-022-09679-3
  41. 10.1007/s12124-022-09679-3
  42. 10.1080/0952813X.2014.895113
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