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Motivation - Coggle Diagram

- - - - ""
        
        reference for explaining IoT briefly and with an emphasis to smart devices right from the start
    - - how to give the emphasis to the smart devices:
        Focus on personalized, user-driven applications of IoT, such as:
        Health monitoring through wearable devices.
        Home automation via connected lighting and appliances.
        Security via smart locks and cameras.
  - - - somthn like briefly after the IoT and smart devices boom, or, amidst the smart devices boom, another technology(concept?) exploded - Digital Twins, which take advantage of the IoT sensors to expand on the scope of collecting data about the device for remote monitoring and control, and use the IoT sensors' data to create virtual models of physical devices or systems (provide an example), which allows for simulation, that is testing scenarios with the virtual counterpart without compromising the physical one (provide examples - at least write them down here), as well as prediction, that is using models to anticipate future states or failures, and also analyzing data and suggesting changes to improve performance. Then say somthn like As such, DT is a technology that offers even more possibilities and growth potential, but that also means that logically in order to meet these goals, it requires even greater amounts of data, for building accurate digital replicas of devices, for areas such as ---- here mention some of the areas where DT tech is used. Maybe have a sentence that mentions some of the latest DT booms.
        
        reference for the boom of IoT with emphasis on smart devices: 1- Security and Privacy in Internet of Things (IoT) Environments; 2- Review of Security Threats and Attacks on IoT-based New Age Ecosystems; 3- Coursera
        
        final result: ""
        
        reference for the boom of DT among the landscape of IoT (in reality it emerged a long time ago but the boom was now)
        
        reference for when you say that IoT is about collecting data/real-time monitoring and control/immediate and basic analysis: 1 - Review of Security Threats and Attacks on IoT-based New Age Ecosystems; 2 - Internet of Things (IoT): Origins, Embedded Technologies, Smart Applications, and Its Growth in the Last Decade, 3 - Toobler, "What Is The Difference Between Digital Twins And IoT"
        
        reference for explaining that DT expands on the scope of collection of data and enters the realm of simulations and other use cases of DT that go beyond IoT by having a rich and contextual virtual reprensentation of the physical counterpart: 1 - Toobler, "What Is The Difference Between Digital Twins And IoT"
        
        reference for the areas where DT are most used today and the latest DT booms.
    - - Digital Twin is a cutting-edge technology that has revolutionized the industry by mirroring almost every facet of a product, process, or service. It has the potential to replicate everything in the physical world in the digital space and provide engineers with feedback from the virtual world [7]. As a result, the technology enables companies to quickly detect and solve physical problems, design and build better products, and realize value and benefits faster than previously possible. - "Digital Twin: Benefits, use cases, challenges, and opportunities"
- - - - it used to say service providers like tech giants (ex Google and Facebook) instead of OEMs but it has to be OEMs - cant talk about digital data giants, can only talk about analog data giants (OEMs) for examplifying the data security concerns.
        So i have to find a reference that isnt Cambridge Analytica because that's for digital data...and a reference just for the part where i say that OEMs keep users data in data siloes
        
        something like this:
        
        ""
        
        references:
        
        reference for OEMs keeping smart device data in centralized data siloes that are prone to data breaches - already have this reference (check the other coggle)
        
        reference for an OEM example and if possible, an analog data breach/attack (Tesla is an example of an OEM)
    - - Filipe asked if i meant "personal data stores" instead of "clouds". Also, regarding the whole thing he says it's basically his paper - check it
        
        something like this:
        
        ""
        
        references:
        
        references for the technologies that allow to protect data and allow users to control it (Bockchain, edge computing, anything else? anything about personal data clouds that Filipe corrected to stores?)
    - - Provide example - not just Prifina but something that mentions rightful compensation (i think there's something in the other coggle)
        
        something like this:
        
        ""
        
        references:
        
        reference for the movement of users claiming rightful compensation and data ownership (there's something in the other coggle) - if possible, when the movement started and what it is more or less about (it's important to understand why users are being wronged, obviously if they give away their data in exchange for a service it makes sense, but should they be further compensated for the data? what are the relevant questions here? and why is it so important to give users control over their data back?)