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conversation about IoT, Digital Twins, problems and user-centric solutions…

- - - - 1 Definition:
        
        Internet of Things (IoT) is one of the mixtures
        of such multiple existing technologies, which incorporates multiple technical fields such as sensors, the Internet, software, real-time operating system (RTOS), embedded systems, etc. The idea of IoT is to act as a bridge that
        connects physical things from the real world to the virtual world through the
        Internet.
      - 2 Definition:
        
        IoT is a large networking platform for interaction and control of multiple
        electronic tools via the Internet. In simple words, it is a combination of sen
        sors, processors, and then controllers for actuation, which all communicate
        through the use of the Internet.
      - 3 Definition:
        
        This idea expands the horizon of
        IoT which now, with few advanced types of equipment, can be implemented
        in almost every sector; for example, self-driving cars, medical recordings,
        smart home systems, manufacturing to customer care, irrigation systems,
        educational institutions, e-commerce, and so on.
      - IoT would see its emergence during 2008-2009 [3]. The first international
        conference of IoT was held in Zurin in 2008
      - Today, IoT is one the most rapidly growing fields in technology with vast
        applications in business, economics, health care, industry, power and energy,
        electric vehicles, and so on.
      - The Internet of Thing is significant cause of the big data; it provides a massive amount of devices linked to the network, enabling ―anytime, anywhere‖ access to information. It implies that these devices can be managed from the web and in turn; provide information in real time, allowing the
        interaction with people who use it. As a phenomenon which has more profound impacts on our society than most others, the IoT can be viewed in all industries, security, transportation, transport, agriculture, education, healthcare,
        public departments, and families, and many other
        domains.
    - - Internet of Things is a new revolution of the Internet. Objects
        make themselves recognizable and they obtain intelligence by
        making or enabling context related decisions thanks to the fact
        that they can communicate information about themselves.
  - - - perguntar ao chat do subcapitulo sobre communication technology that allows connections between devices.
      - The data streams, from the sensors or any
        other smart devices that acknowledge the change in environmental factors,
        get stored up in a common platform where the necessary information gets
        processed, computed, and analyzed
        (meter um diagrama simples maybe, este paper tem)
      - In a smart home system, multiple sensors are embedded in different
        locations of the house that tracks down the changes in a state like temperature,
        lighting, air quality, etc. These sensors are the starting point in the system
        whose data are then collected to a virtual cloud via the Internet. The data
        in the cloud is then processed and filtered after which the processed data is
        analyzed in real time. The endpoint to this system can be the APIs or the
        controllers in the home itself.
      - Technical Details of IoT
        
        About processing:
        For example,
        IoT-based systems can be real time, where data is collected and processed in
        real time. These systems are generally process monitoring systems such as
        monitoring the temperature in a room, the pressure inside a chemical reaction
        chamber, monitoring the heart rate and blood pressure of a medical patient,etc.
        On the other hand, IoT systems also have to deal with non-time critical data
        such as soil/humidity moisture from agricultural farms. These data can be
        stored in a database, possibly in a data center, and can be processed later
        on.
        
        Because of the nature of real-time systems, it has become necessary to
        add computing power near the source of data so that the latency is minimized
        as much as possible. Thus, two topologies are naturally born from this: on-site
        processing and off-site processing [17]. On-site processing refers to the data
        processing that occurs at the source itself. Here, the sensors are coupled with
        devices that have significant processing capabilities. The data
        collected can be shared in the IoT system at a later time.
        
        On a similar note, we have off-site processing. Here, the processing is
        done remotely, i.e., not at the source of the data. The data generated at the
        source has to be transmitted somehow to the processing site where it is
        processed and the processed results are then transferred to the users.
        As
        an example, consider a retail store that changes its goods based on customers’
        preferences. For this, the data of customers’ preference of items are logged.
        Off-site processing is preferable for this since the store needs to collect a large amount of data from the customers before ordering new goods in the store.
        The data logged
        in a day can be sent to a cloud service, such as an item recommendation
        system, which can perform data analysis on the customer data to figure out
        the customer preferences and the kinds of items that customers are potentially
        looking for. The cloud service can also be made available to be used by
        other retail stores. This way, every store does not need to deploy its item
        recommendation system and can use pre-existing ones, thus saving a large
        amount of money and time.
      - What makes things be smart?
        "becoming smart, they can be connected to the
        Internet and can provide us with valuable data about their usage. This data
        can be accessed from anywhere in the world through the Internet."
    - - What makes things smart?
        Internet of Things is a new revolution of the Internet. Objects make themselves recognizable and they obtain intelligence by making or enabling context related decisions thanks to the fact that they can communicate information about themselves
        The lowest layer is made up of smart objects integrated with sensors. The sensors enable the interconnection of the physical and digital worlds allowing real-time information to be collected and processed. There are various types of sensors for
        different purposes. The sensors have the capacity to take measurements such as temperature, air quality, speed, humidity, pressure, flow, movement and electricity etc.
    - - IoT devices, which range
        in size from tiny wearables to massive machinery and are outfitted with actuators and
        sensors, can intelligently sense their environments and take action on their own
  - - - :pencil2:
        Introduction to IoT
        Asim Maharjan and Saju Khakurel
        
        Domestic Applications:
        (Household Monitoring, Waste Management and Home Security)
        
        Household monitoring is one of the most known examples of IoT
        
        With the help of IoT, people can monitor various equipment in their homes, such as lights and other electronic appliances. With advancements in technology and several everyday household appliances like refrigerators, television, etc., becoming smart, they can be connected to the Internet and can provide us with valuable data about their usage. This data can be accessed from anywhere in the world through the Internet. Another one of the major applications is switching, i.e., the act of powering ON/OFF devices through the internet. With this, we can effectively control our house from anywhere in the world.
        
        As an example, web interfaces can be built, through which you
        can change the temperature of your smart heating system, control the room temperature of your smart AC, turn OFF the light, view your electricity usage, and many more.
        
        Healthcare:
        
        IoT has a wide range of applications in the health industry. The term Internet of Medical Things (IoMT) was introduced to specifically refer to the application of IoT in healthcare
        
        With IoT-enabled devices, remote health monitoring and emergency notification systems can be put to use
        
        Devices for heart rate
        monitoring are present today in the form of smartwatches and are capable
        of providing sophisticated levels of information such as heart rate, irregular heartbeat notifications, ECG reports, and even sleep monitoring. The devices
        can also be used to provide medical information, such as the dosage and when to take it, and alerts as well as for monitoring whether a patient has
        taken the medicine or not. Through the use of IoT, the data generated by such devices can be provided to doctors and physicians who can analyze them and provide better medical diagnoses to the patients. It also allows people to monitor themselves their own health conditions and improve their lifestyles to achieve better health.
        
        Machine learning in combination with IoT can provide a very powerful tool for medical diagnosis. In [12], the authors have proposed a predictive machine learning algorithm for the detection of heart diseases by using data such as blood pressure, heart rate, respiratory rate, and blood sugar.
        
        E-commerce:
        
        check with chat what does it mean to have IoT in retail shopping - stores and restaurants, cause i didnt really get it (page 40)
        
        With the help of IoT, the information
        of each and every item in the warehouses can be made available, and product identification and tracking in each stage in supply chain management can be achieved using RFID [26]. Data such as temperature, humidity, etc., are of much importance when the storage of goods is concerned.
        
        Industry:
        
        Manufacturing: In the industrial sector, IoT is better known as the industrial Internet of Things (IIoT). IIoT represents what is known as Industry 4.0 [28], the new revolution in the industrial sector brought on by the use of IoT, data analytics, cyber-physical systems (CPS), cloud computing, edge computer, and other
        modern technologies. Many technologies related to IoT such as wireless sensor networks (WSNs) and RFID are heavily used for the identification and
        tracking of goods in industries. WSNs enable industries to accurately sense and monitor their environmental conditions by utilizing a network of sensors placed throughout the manufacturing plant [29]. It allows them to monitor the present conditions and make necessary changes to get maximal product output.
        
        Besides manufacturing, IoT also provides a lot of benefits in the agricul
        tural sector. A large number of sensors connected can provide farmers with
        data such as soil humidity, temperature, and pH levels of the entire farm.
        This allows the farmers to make proper adjustments to the ever-changing
        environment to get better crop yields.
        
        Generally speaking:
        
        These systems do
        not possess any delay, minimize human effort by expanding the independence
        of humans, efficiently utilize the resources, save time, and are transparent.
        This system allows the user to make changes in
        their homes when no one is physically present there or just monitor the activ
        ity that is taking place at the home when they are away
        
        Energy:
        
        These systems monitor the power consumption
        and allow the users to visualize the energy usage of their households and buildings. This allows people to more efficiently utilize their electricity consumption by preventing unnecessary usage of electrical appliances
      - :pencil2:: Internet of Things-IOT: Definition, Characteristics, Architecture, Enabling
        Technologies, Application & Future Challenges
        
        Smart Living:
        Smart Home
        Appliances: Refrigerators with LCD screen telling what’s
        inside, food that’s about to expire, ingredients you need to buy
        and with all the information available on a Smartphone app.
        
        Smart Cities:
        Smart
        Parking: Real-time monitoring of parking spaces availability
        in the city making residents able to identify and reserve the
        closest available spaces
        
        Smart environment:
        
        Protecting wildlife:
        Tracking collars utilizing GPS/GSM modules to locate and
        track wild animals and communicate their coordinates via
        SMS.
      - :pencil2: Security and Internet of Things: Benefits, Challenges, and
        Future Perspectives
        
        Wearable technology with devices to monitor and
        share a person’s behavior and health information is one such business that is providing
        wearable technology. IoT apps and gadgets are being made available to patients in the
        healthcare industry
      - :pencil2: Human Digital Twin for Fitness Management
        
        In particular, health and wellness applications have emerged as a fast-growing category of smart applications based on the use of wearable devices. This increasing trend is considered as a prompt and useful resource for collecting users’ data that are exploited for generating recommendations for a healthy lifestyle.
        (use this to say that for now my work will focus on wearable devices)
  - - - The whole idea of IoT stands on data entry, its manipulation, and necessary actions, but with the wide application area and increasing data levels including some confidential information too, the future of IoT leans toward complicated security and privacy issues.
      - From a technological perspective, IoT faces
        challenges such as interoperability (With a large number of IoT systems being deployed, there is a higher chance of interoperability issues, i.e., integration of different systems into a single one. In addition to this, privacy concerns also arise when we have devices that can monitor our daily activities and transfer that data through a large network. Any device that is connected to the Internet is susceptible to many different forms of attack that involve stealing one’s identity, accessing other people’s data, and so on.
    - - Compensation for users that agree to the collection of their data (i think - check with chat)
        Participating in MCS is usually costly for individual workers, since it consumes not only workers’ time but also the system resources (e.g., battery, computing power) of their mobile devices. Therefore, it is essential to design incentive mechanisms to stimulate worker participation. Typically, an incentive mechanism selects a subset of workers from the pool of potential participants to execute sensing tasks, and determines the payments to them that effectively compensate their participation costs.
  - - - Conclusions:
        IoT is a technology with vast applications in many
        fields that affect our day-to-day lives. Improvements brought in the fields of healthcare, industries, energy management, etc., by the sensing, monitoring, and communicating capabilities of IoT have greatly upgraded our lifestyle and it will keep on enhancing our lifestyle in the future as the IoT technology further evolves. However, IoT is still not a technology that is without faults. Many technical and ethical issues arising from the use of IoT have hindered it from its widespread adoption.
      - Businesses sharing the users' personal data - doing business out of users' personal data when the users get nothing.
        As an example, consider a retail store that changes its goods based on customers’ preferences. For this, the data of customers’ preference of items are logged. Off-site processing is preferable for this since the store needs to collect a large amount of data from the customers before ordering new goods in the store. Also, the store can use pre-existing systems for this task. The data logged in a day can be sent to a cloud service, such as an item recommendation system, which can perform data analysis on the customer data to figure out the customer preferences and the kinds of items that customers are potentially looking for. The cloud service can also be made available to be used by other retail stores. This way, every store does not need to deploy its item recommendation system and can use pre-existing ones, thus saving a large amount of money and time.
    - - "Wealth of intelligence" :
        These interconnected objects have data regularly collected, analyzed and used to initiate action, providing a wealth of intelligence for planning, management and decision making. This is the
        world of the Internet of Things (IOT)
        (could lead to the point where consumers make nothing)
    - - THE rapid proliferation of mobile devices with diverse
        sensing capabilities has significantly expanded the bound
        aries of sensory data acquisition. This, combined with the
        widespread adoption of machine learning and artificial intel
        ligence, has led to remarkable successes across various indus
        tries and applications. With the emergence of the Internet of
        Things (IoT) and its vast data availability, IoT data trading and
        sharing have become prevalent, offering numerous benefits to
        researchers, city planners, businesses, and individuals [1]. In
        the big data economy, it has become common for individuals
        to exchange their IoT data for free virtual services offered by
        Internet giants like Facebook, Twitter, and Amazon [2].How
        ever, concerns regarding data privacy disclosure and a growing
        awareness of the economic value of IoT data have motivated
        individuals to seek monetary compensation for sharing their
        data [3]. Studies have estimated the value of each user’s data
        to companies like Google and Facebook, further fueling the
        demand for fair compensation [4]. In response to this emerging
        trend, several startup companies such as CitizenMe, Datacoup,
        and CoverUS have pioneered the model of IoT data circulation,
        paying data owners for accessing their personal data [5], [6],
        [7]. This has given rise to data markets where IoT data privacy
        is bought and sold.
    - - To fuel AI reasoning, vast amounts of high-quality data are
        required– largely biometric, generated by the internet of things (IoT) sensors, from which personal behavioural patterns can be decoded. The current data science approach resides on the concept of collecting data into centralised data hubs for analysis. It combines the technologies of smart sensors streaming data through high-performance networks, storing vast amounts of data in data lakes and using reasoning on data with supercomputers.
        Data collecting concepts provide essential property rights in the hands of data collectors and
        putdataproducersinthepassiverolewithonlylimitedornorights(Wagner,2020).Research,
        based on data collecting raises significant ethical and social concerns (Letheren et al., 2020;
        Mobilio, 2020; Nath and Sahu, 2020).
        Currently, data collecting concept is formatted to fill the AI needs for detailed data, where IoT
        dataarecollected andstoredincentraldatalakes,excludingdataproducersatthefirststepin
        the process (Perko, 2020).
        IoT biometric data collecting: Currently, data are collected in big data siloes, utilised by organisations capable of storing
        and analysing big data, such as governments, large companies and research organisations,
        following different goals from social control, profit-related activities and open research.
        3.1 Data collecting
        In data collecting concept, data consumers, such as information communication technology
        (ICT) services providers, social media companies or security organisations and researchers,
        govern data-related processes, mostly due to their direct interest to utilise data for achieving
        their organisational goals, ranging from weather predictions, marketing, smart city
        management, drug development, selling data and analysis results, etc. They are
        optimising data collecting, storing, data analysis and data use with the premise to
        optimise the process and raise data quality properties. Since data are considered an asset for
        data consumers, the collected data are rarely shared, whereas data producers are excluded
        fromtheprocess.Theprocessedinformationintheformofprediction,prescriptionsormental
        models is used in internal processes or shared with other stakeholders in HyR ( Hybrid reality is a brief, dynamic unstable period in which people and artificial intelligence (AI) technology coexist and affect each other.). Moreever,data producers are
        generally completelyunawareoftheoperationaldynamicsofdatacollectingandareunableto
        actively participate in the HyR interactions.
    - - It is often said that marketing needs to be data-driven (e.g., Wedel & Kannan, 2016). As the process of digitization reduces the costs of collecting, parsing, and storing data, it allows many areas of marketing to embrace data to an unprecedented degree (Goldfarb & Tucker, 2019b). It is not just marketing that has benefited, but also broader innovation across product categories (e.g., Manyika et al., 2011). Consumer data is increasingly a foundation on which firms build their business models to compete in sectors such as health, advertising, security, e-commerce, transportation, and banking (Jia, Jin, & Wagman, 2018). Firms use consumer data for everything from the development of new ideas for products and services (e.g., Porter & Heppelmann, 2014) to selling them to prospective target customers (e.g., Bleier & Eisenbeiss, 2015b).
        (has concrete examples of how some big companies like Google, profit from individual data)
- - - - :pencil2: Human Digital Twin for Fitness Management
        
        Some of the latest IoT developments include technologies for home, health, transportation, and environment monitoring. In particular, health and wellness applications have emerged as a fast-growing category of smart applications based on the use of wearable devices. This increasing trend is considered as a prompt and useful resource for collecting users’ data that are exploited for generating recommendations for a healthy lifestyle.
        Together with these advances, the synergic action of ubiquitous connectivity, spread sensor technologies, advances in artificial intelligence (AI), big data analytics, cloud computing, and shared databases (distributed in the cloud) has motivated the development of the industrially diffused Digital Twin (DT) technology [1]. In the fields of aviation and manufacturing, where DTs are nowadays being massively developed and used, a DT is defined as the virtual (digital) counterpart of a physical system. The DT starts living as the physical is being prototyped, dies when it is disassembled, and follows its physical twin during its whole life, resembling its status and being continuously connected and synchronized with it. Thanks to AI, the DT continuously controls and monitors its physical twin status, with the aim of optimizing its performance by triggering self-optimization and self-healing mechanisms.
        
        JOINS IOT WITH DT AND AI ALL IN ONE PARAGRAPH
  - - - The DT receives data from its physical twin, reconfigures itself to be synchronized with it, applies AI algorithms to detect anomalies and then suggests self-healing or optimization actions.
        Thanks to the DT, all stakeholders have a quick and easy access to the physical object status, to monitor and control it and eventually trigger required actions.
      - The success of DT technology in manufacturing, documented in the extensive survey reported in [4], has motivated several studies aimed at extending it to humans, by designing human DTs, that is computer models of humans tailored to any patient to allow researchers and clinicians to monitor the patient’s health, for providing and test treatment protocols
  - - - Digital twins are poised to enter our lives with Industry 4.0. The Digital Twin Network (DTN) paradigm is projected to deliver upon the promise of efficient collaboration among digital twins to enable complicated and systematic services across many domains, through depicting an overall picture of a group of physical objects
      - The master digital twin aggregates the processed data from worker digital twins to model the DTN continuously for user query services
        (use this to say these authors are an example of how aggregating DIgital Twins is already an existing desire)
    - - Results show that, thanks to the team of DTs, SmartFit computes trustable predictions of the physical twins' conditions and produces understandable suggestions which can be used by trainers to trigger optimization actions in the athletes' behavior.
        (this could go to say that having a team of DTs has great benefits, which justifies our desire to create a PDT which is essentially a team of DTs)
  - - - We expect the physical, biological, and cyber worlds to be fused together via the new generation of intelligent connectivity. In such an era, everyone may have his or her own Personal Digital Twin (PDT) in the cyber world. Such a PDT may include the person’s external appearance, as well its internal organs and tissues. The PDT may be used to predict human health, behavior, and emotion in advance of developments warranting concerns or requiring attention, and even simulate people’s thoughts to realize spiritual immortality in some extreme sense.
    - - The exponentially growing amount of digital information and data analysis increase the ability to perceive the holistic situation of people. This article applies the digital twin paradigm to strengthen a person’s ability to utilize information about themselves by creating a digital representation of their situation to support their well-being. More specifically, we propose a blueprint to empower individuals by improving their self-determination regarding their personal data. The blueprint will help service and data providers, both public and private, to develop a common understanding of the role and possibilities of a citizen’s controlled personal digital twin of themselves—a citizen digital twin (CDT)—for creating people-centric solutions.
        (use this to say, "similarly, this work suggests a PDT concept that empowers individuals by offering a structure that contains individuals' data to build a holistic digital replica of individuals that is meant to be owned and controlled by them, and whose purpose is to be able to empower an AI component in the sense that it can provide it with a holistic data pool of that individual and as such, can offer support to a personal AI assistant that, having access to health data and others, can offer suggestions and predictions on various aspects of the person's life. Even though the idea of this work goes through offering a PDT model composed of various dimensions of an individual, the focus of the work for now is around the data that is collected from wearable smart devices and as such the practical part is about trying to aggregate Digital Twins of wearable devices in one single Digital Twin - the Personal Digital Twin.)
      - The basic idea behind the CDT is to help people to form a big picture of their own lives. The CDT helps a person perceive their own situation and to become empowered to act for their own good.
        The CDT depicted in this article is a citizen’s own tool, like a mirror through which a citizen creates a digital representation of themselves to increase awareness and understanding of their own situation and multi-dimensional well-being. By well-controlled sharing the information to service providers, the citizen can receive suitable services from service ecosystems at the right times. It particularly concerns psychological and social elements of well-being.
      - However, the DT of a citizen is a new idea and scientific research on the topic is, therefore, lacking.
      - What this work is lacking in comparison to mine! AI
        i m pretty sure their work on CDT is about giving people the opportunity to see their whole lives through their CDT and hence be able to reflect on it, being the reflection their ultimate goal for their CDT, whereas for me, the ultimate goal is to provide people with they're very own personal life assistant.
    - - user-centric HDT - check this out
- - - - To fuel AI reasoning, vast amounts of high-quality data are
        required– largely biometric, generated by the internet of things (IoT) sensors, from which personal behavioural patterns can be decoded. The current data science approach resides on the concept of collecting data into centralised data hubs for analysis. It combines the technologies of smart sensors streaming data through high-performance networks, storing vast amounts of data in data lakes and using reasoning on data with supercomputers.