Mobility and Ubiquity

Emergent Technologies & Media (ETM)

Andy Weeger

Neu-Ulm University of Applied Sciences

September 23, 2025

Revision

Characteristics of emerging technologies

Rotolo et al. (2015) outlines five attributes that classify emerging technologies and differentiate them from other technologies:

1. Radical novelty
   
2. Relatively fast growth
   
3. Coherence
   
4. Prominent impact
   
5. Uncertainty and ambiguity
   

Stages of emergence

Pre-emergence, emergence, and post-emergence: attributes and ’stylised’trends. (Rotolo et al., 2015, p. 1833)

Interconnectedness

Interconnectedness refers to a formal linkage between two different systems.

Computer networks reflect a collection of computers and devices connected so that they can share information and services. They, thus, are the clue of (interconnected) information systems.

Zimmerman (2001)

Effects

Emergent digital technologies facilitate more strongly interconnected systems, as they enhance

networking infrastructure, connectivity capabilities, and interoperability (e.g. through standardization).

Examples of emergent technologies driving interconnected systems are
5G and IoT ecosystems (e.g., Matter smart homes) and cloud-native microservices architectures (e.g., containers and orchestration platforms)

Distributed systems

A distributed system is a collection of independent computers that appear to its users as a single coherent system.

The independent computers, also known as nodes, communicate and coordinate their actions by passing messages as they do not share a common memory.

Andrew S et al. (2002)

Effects

Emergent digital technologies drive and are driven by distributed systems as they they provide the necessary infrastructure for e.g.,

scalability and efficiency, fault tolerance and reliability, real-time processing, data privacy and security, and cost-effectiveness.

Examples: Edge computing, distributed AI/ML, distributed ledger technologies and consensus algorithms, and serverless computing

As digital technologies continue to evolve, the role of distributed systems will only become more critical in enabling innovative applications and services across various industries.

Jogalekar & Woodside (2000), Attiya & Welch (2004), Andrew S et al. (2002), Sunyaev (2020)

Hypothesis 4

Emerging information technologies enable mobile and ubiquitous systems.

Mobility

Discussion

How would your life look like without a mobile phone?

For which tasks and activities do you heavily rely on mobile computing?
Imagine what you would do if you would not have access to a smartphone.

10:00

Definition

Mobile computing

Using portable devices in wireless-enabled networks to perform computational tasks and access network services on the move (e.g., anyplace, and anytime)

Forman & Zahorjan (1994)

Discussion

What marks the breakthrough of mobile computing?

Miniaturization of computing technology

The miniaturization of transistors and integrated circuits during the mid-20th century laid the foundation for smaller, more portable computing devices. This paved the way for the development of laptops and eventually smartphones.

Cellular network development

The establishment of cellular networks in the 1980s enabled mobile devices to connect and transmit data wirelessly. This provided the critical infrastructure for mobile communication and internet access, a cornerstone of mobile computing.

Personal Digital Assistants (PDAs) in the 1990s

PDAs like the Palm Pilot offered basic computing functionalities like calendars, contacts, and note-taking in a portable format. These devices bridged the gap between bulky laptops and mobile phones, paving the way for the widespread adoption of pocket-sized computing.

The rise of touchscreen interfaces and smartphones with advanced operating systems (late 1990s and early 2000s)

The introduction of touchscreen interfaces and user-friendly operating systems like iOS and Android on devices like the iPhone and Blackberry revolutionized mobile computing. These advancements made mobile devices more intuitive and accessible, leading to mass adoption.

Key components

Mobile computing is not simply a miniaturisation of conventional computer technology. It is a complex ecosystem with several key components as enablers:

Mobile devices, wireless networks, mobile first operating systems, mobile applications, and the related ecosystems (e.g., app stores, edge computing).

Mobile devices

The foundation of mobile computing lies in portable devices like smartphones, tablets, and laptops. These devices boast increasingly powerful processors, improved battery life, and high-resolution displays, enabling them to handle complex tasks and deliver rich multimedia experiences.

Wireless networks

The invisible threads that connect mobile devices to the digital world are wireless communication technologies. Cellular networks, Wi-Fi, and Bluetooth provide the critical infrastructure for data transmission, enabling seamless access to information and services.

Operating systems

The operating system acts as the maestro of the mobile computing symphony. Popular options like Android and iOS provide a user-friendly interface, manage hardware resources, and facilitate communication between applications and the device.

Mobile applications

The true stars of the mobile computing show are applications, downloadable from app stores. These applications offer a vast array of functionalities, from communication tools like social media platforms to productivity suites and entertainment options like games and streaming services.

See e.g., Stojmenovic (2002) and Othman et al. (2013)

Exercise

Select on of the sectors listed below and work on following tasks:

• Identify three ways mobile computing has already transformed their assigned sector.
• Predict two significant changes that will likely occur in their sector in the next years based on emerging mobile technologies.
• Propose one innovative mobile solution to an existing challenge in their sector.

Be prepared to present your findings.

Sectors: healthcare, education, retail, transportation, finance/banking, entertainment, agriculture, manufacturing, and tourism

20:00

Effects

As an emerging technology, mobile computing has had a significant impact on multiple levels and undoubtedly transformed our lives.

Increased productivity, improved communication and collaboration, enhanced access to information and entertainment, and new business models and social interactions.

See e.g., Ladd et al. (2010)

Challenges

However, mobile computing also comes with some challenges:

Digital divide, security vulnerabilities, health concerns, and impact on social interactions.

Digital divide

Unequal access to technology and infrastructure

Security vulnerabilities

Protecting data and privacy

Health concerns

Excessive screen time and addiction

Impact on social interactions

Face-to-face communication decline

See e.g., Wareham et al. (2004) and Dryer et al. (1999)

AI x XR x Mobile Computing

Reflection

Will AR glasses become the next primary computing platform?

• What technological hurdles still need to be overcome before AR glasses could replace smartphones as our primary computing device?
• Which tasks that would be fundamentally transformed if AR glasses became our primary computing interface?
• How might widespread adoption of AR glasses affect social interactions, privacy, and the challenges we’ve discussed?

Discuss the questions in small groups and be prepared to present and discuss your findings.

20:00

Summary

Mobile computing established the behavioral and infrastructural foundations for pervasive digital environments:

Portability, always-on connectivity, context introduction, ecosystem model, and user adaptation.

Portability

Miniaturized hardware freed computing from fixed locations, making digital interaction a constant companion.

Always-on connectivity

Cellular networks and Wi-Fi normalized the expectation of continuous network access—anywhere, anytime.

Context introduction

Location-aware services (GPS, cell tower triangulation) introduced users to context-sensitive computing.

Ecosystem model

App stores and cloud backends established patterns for software distribution and seamless updates across devices.

User adaptation

Daily smartphone use trained billions of users to interact with networked, sensor-rich, context-aware systems.

Forman & Zahorjan (1994), Satyanarayanan (2001), Qi & Gani (2012)

Ubiquity

Definition

Ubiquitous computing integrates computation into the environment, rather than having computers which are distinct objects.

The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it. Mark Weiser, American computer scientist and chief technology officer (CTO) at Xerox PARC

Weiser (1991), Weiser (1993)

Characteristics

Ubiquitous computing (UC), also known as ubicomp, is characterized by several key features that differentiate it from traditional computing:

Invisibility, context-awareness, connectivity, and situated and proactive interaction.

Invisibility

Unlike a bulky desktop computer, ubiquitous computing aims to integrate technology seamlessly into our surroundings. Think smartwatches, voice assistants, or embedded sensors in clothing or furniture. The user interacts with the technology naturally, without being hindered by the physical device itself.

Context-awareness

Ubicomp systems gather data about the user’s environment and situation. This allows for a more personalized and relevant user experience. For example, a fitness tracker might suggest workout routines based on the time of day and your activity level.

Connectivity

Ubiquitous computing thrives on a network of interconnected devices. This network could include smartphones, wearables, sensors, and even appliances. The seamless exchange of data between these devices allows for a more intelligent and responsive environment.

Proactive interaction

The ultimate vision of ubiquitous computing is for systems to not only react to user input but also anticipate their needs. Imagine a system that automatically adjusts lighting or temperature based on your preferences and the time of day.

Weiser (1994), Norman (1998), Dey (2001), Satyanarayanan (2001)

Evolution

From mainframe
to personal computer
to ubiquitous computing.

Mainframe: one computer shared by many people

Personal computer (PC): one computer, one person

Ubiquitous computing (UC): lots of computers, used by individual users, partly shared

Mainframe: Computers were a scarce resource run by experts behind closed doors. PC: You have your computer, it contains your stuff, and you interact directly and deeply with it

UC systems

Ubiquitous computing systems rely on tiny computing devices which vanish into the environment¹ and adapt dynamically to it.

These tiny computers need to be…

• networked, distributed, and transparently accessible,
• context-aware to optimize their operation in the respective environment,
• capable of acting autonomously, without human intervention, and
• able to manage a variety of dynamic activities through intelligent decision-making.

UC vs. virtual reality

Ubiquitous computing is roughly the opposite of virtual reality.

Where virtual reality puts people inside a computer-generated world, ubiquitous computing forces the computer to live out here in the world with people.

Example

Exercise

What are other examples of ubiquitous computing?

Reflect the characteristics and name the main technological enablers.

15:00

Context

Context is any information that can be used to characterize the situation of an entity.

An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves.

Dey (2001)

Context-aware computing

A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task.

Following contexts need to be considered:
user context, environmental context, social context, and service context.

User Context

User context refers to the information that describes an individual user and their current situation. This information helps the system tailor its behavior to the user’s needs and preferences. Here are some key aspects of user context:

• Identity: Who the user is, their role, and their preferences. For example, a learning platform might recommend different courses based on the user’s educational background and interests.
• Location: Knowing the user’s location allows for context-aware services like suggesting nearby restaurants or providing personalized traffic updates for navigation.
• Activity: Understanding the user’s current activity, such as working, exercising, or sleeping, enables the system to adapt its behavior. For instance, a fitness tracker might suggest workout routines based on the user’s activity level or a smart assistant might prioritize work-related notifications during office hours.
• Time: The time of day can be relevant context. Smart lights might adjust based on the time or a calendar app might remind you of upcoming events.

Environmental context

Environmental context refers to the physical surroundings where the user interacts with the system. Sensors and other data sources can provide information about the environment to create a more responsive experience. Here are some examples of environmental context:

• Temperature: Sensors can detect room temperature and adjust a smart thermostat accordingly.
• Lighting: Smart lighting systems can adapt brightness and color temperature based on the ambient light levels.
• Noise level: A smart speaker might adjust its volume based on the prevailing noise level in the environment.
• Proximity to other devices: Ubicomp systems can leverage the presence of other devices to provide context. For example, unlocking your phone might automatically unlock your smart door lock.

Social context

Social context refers to the social environment surrounding the user. This includes the presence of other users and their interactions. While still under development, Ubicomp systems are exploring ways to understand social cues to further personalize the experience. Here are some possibilities for social context:

• Presence of other users: A smart meeting room might adjust its settings (lighting, temperature) based on the number of people present.
• Social interactions: Smart devices might even be capable of understanding social cues like gestures or facial expressions in the future, potentially adjusting volume or suggesting activities based on the social mood.

Service context

Service context refers to the characteristics and capabilities of the services available in a particular environment. Here’s how service-context works alongside other contexts:

• Understanding service capabilities: Service-context focuses on what services are available, their functionalities, and any limitations. For example, a navigation app might consider traffic information and available routes as part of the service-context when suggesting directions. It wouldn’t recommend a route that requires a specific service (like a high-occupancy vehicle lane) if the user’s car isn’t eligible.
• Interaction with other contexts: Service-context interacts with other contextual factors like user context and environmental context. A smart assistant might consider the user’s location (user context) and available delivery services (service-context) before suggesting restaurants for food delivery. Similarly, it might adjust its recommendations based on the time of day (user context) and peak service hours (service-context).
• Dynamic service selection: Service-context allows Ubicomp systems to dynamically select and utilize the most appropriate service for a given situation. Imagine a scenario where you need to print something. The system might consider available printers (environmental context) and their functionalities (service-context) like color printing or duplex printing. It would then choose the most suitable printer based on your document and the available services.

Dey (2001)

Discussion

How is context-awareness implemented in your example(s)?

Summary

As computing devices fade into the environment, the underlying infrastructure remains—and scales.

Miniaturization, connectivity, software orchestration, sensing, and cloud and analytics.

Miniaturization

Processors shrink from pockets into objects, textiles, and environments, enabling invisible computation.

Connectivity

Wireless networks (cellular, Wi-Fi, Bluetooth, mesh) provide the fabric linking distributed computation.

Software orchestration

Cloud-native deployment, edge computing, and over-the-air updates enable software to flow across distributed environments—no longer bound to individual devices.

Sensing

Embedded sensors (accelerometers, GPS, biometrics, environmental) provide the context-awareness that enables ambient intelligence.

Cloud and analytics

Centralized processing, storage, and big data analytics persist as the backbone for distributed, intelligent environments.

Huang & Wu (2017), Choi et al. (2013), Schilit et al. (1994)

Synthesis

Two paradigms, one trajectory

Mobile computing and ubiquitous computing represent two evolutionary stages in the relationship between humans and technology.

Mobile Computing

• Focus: Device portability
• User attention: Explicit interaction
• Model: Anywhere, anytime
• Visibility: Device-centric
• Context: User carries context

Ubiquitous Computing

• Focus: Environmental integration
• User attention: Implicit, ambient interaction
• Model: Everywhere, all the time
• Visibility: Invisible
• Context: Environment provides context

Satyanarayanan (2001), Abowd & Mynatt (2000)

From mobility to ubiquity

Mobile computing laid the groundwork for ubiquitous computing by normalizing three critical shifts:

Always-connected expectations

Mobile computing trained users to expect continuous network access, creating the behavioral foundation for ubicomp environments.

Context as a design primitive

Location-aware services on smartphones introduced users to context-sensitive computing, paving the way for richer environmental awareness.

Distributed ecosystems

Cloud backends and over-the-air software deployment (e.g., app stores) established the infrastructure patterns that ubiquitous systems now scale across physical environments.

Dey (2001), Schilit et al. (1994), Choi et al. (2013)

The smartphone as transitional artifact

The smartphone represents a transitional artifact—too visible to be truly ubiquitous, yet too connected to be merely mobile.

• Mobile computing asks: How do we bring computing with us?
  
• Ubiquitous computing asks: How do we weave computing around us?

The answer is the same infrastructure, different visibility.

As computing disperses into wearables, ambient displays, smart environments, and AI agents, the explicit device fades while the computational layer persists.

Lukowicz et al. (2009), Weiser (1991)

Synopsis

Mobile computing established the behavioral and infrastructural foundations—portable devices, wireless networks, app ecosystems, and always-on connectivity. Ubiquitous computing extends this foundation by dissolving the device boundary, weaving computation into the environment through context-awareness, invisibility, and proactive interaction.

Together, they enable and are enabled by information systems characterized by:

Multimodality and immersion, intelligence and affection, as well as interconnectedness and distributivity.

Multimodality and immersion

Natural interaction through various modalities reduces the sense of interacting with machines and enhances the feeling of presence.

Intelligence and affection

AI analyzes multi-contextual data (user, environment, social, service) for adaptive, anticipatory behavior; affective computing enables systems to understand and respond to user emotions.

Interconnectedness and distributivity

Distributed systems communicate and share data seamlessly across devices and environments, creating intelligent infrastructure.

Lukowicz et al. (2009), Satyanarayanan (2001), Dey (2001)

Q&A

Literature

Abowd, G. D., & Mynatt, E. D. (2000). Charting past, present, and future research in ubiquitous computing. ACM Transactions on Computer-Human Interaction, 7(1), 29–58. https://doi.org/10.1145/344949.344988

Andrew S, T., Maarten Van, S., et al. (2002). Distributed systems: Principles and paradigms.-1st. Prentice Hall.

Attiya, H., & Welch, J. (2004). Distributed computing: Fundamentals, simulations, and advanced topics (Vol. 19). John Wiley & Sons.

Choi, M., Park, J., & Jeong, Y.-S. (2013). Mobile cloud computing framework for a pervasive and ubiquitous environment. The Journal of Supercomputing, 64(2), 331–356. https://doi.org/10.1007/s11227-011-0681-6

Dey, A. K. (2001). Understanding and using context. Personal and Ubiquitous Computing, 5, 4–7.

Dryer, D. C., Eisbach, C., & Ark, W. S. (1999). At what cost pervasive? A social computing view of mobile computing systems. IBM Systems Journal, 38(4), 652–676.

Forman, G. H., & Zahorjan, J. (1994). The challenges of mobile computing. Computer, 27(4), 38–47. https://doi.org/10.1109/2.274999

Huang, D., & Wu, H. (2017). Mobile cloud computing: Foundations and service models. Morgan Kaufmann.

Jogalekar, P., & Woodside, M. (2000). Evaluating the scalability of distributed systems. IEEE Transactions on Parallel and Distributed Systems, 11(6), 589–603.

Ladd, D. A., Datta, A., Sarker, S., & Yu, Y. (2010). Trends in mobile computing within the IS discipline: A ten-year retrospective. Communication of Association of Information Systems (CAIS), 27, 285–316.

Lukowicz, P., Pentland, A., & Ferscha, A. (2009). From backpacks to smartphones: Past, present, and future of wearable computers. IEEE Pervasive Computing, 8(4), 18–21. https://doi.org/10.1109/MPRV.2009.82

Norman, D. A. (1998). The invisible computer: Why good products can fail, the personal computer is so complex, and information appliances are the solution. MIT press.

Othman, M., Madani, S. A., Khan, S. U., et al. (2013). A survey of mobile cloud computing application models. IEEE Communications Surveys & Tutorials, 16(1), 393–413.

Qi, H., & Gani, A. (2012). Research on mobile cloud computing: Review, trend and perspectives. Proceedings of the Second International Conference on Digital Information and Communication Technology and Its Applications (DICTAP), 195–202. https://doi.org/10.1109/DICTAP.2012.6215350

Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827–1843.

Satyanarayanan, M. (2001). Pervasive computing: Vision and challenges. IEEE Personal Communications, 8(4), 10–17. https://doi.org/10.1109/98.943998

Schilit, B. N., Adams, N., & Want, R. (1994). Context-aware computing applications. Proceedings of the IEEE Workshop on Mobile Computing Systems and Applications, 85–90. https://doi.org/10.1109/WMCSA.1994.16

Stojmenovic, I. (2002). Handbook of wireless networks and mobile computing. Wiley Online Library.

Sunyaev, A. (2020). Internet computing: Principles of distributed systems and emerging internet-based technologies (1st ed.). Springer Nature Switzerland AG.

Wareham, J., Levy, A., & Shi, W. (2004). Wireless diffusion and mobile computing: Implications for the digital divide. Telecommunications Policy, 28(5-6), 439–457.

Weiser, M. (1991). The computer for the 21 st century. Scientific American, 265(3), 94–105.

Weiser, M. (1993). Hot topics-ubiquitous computing. Computer, 26(10), 71–72.

Weiser, M. (1994). The world is not a desktop. Interactions, 1(1), 7–8.

Zimmerman, R. (2001). Social implications of infrastructure network interactions. Journal of Urban Technology, 8(3), 97–119.

Footnotes

1. They vanish into the environment due to miniaturization and new materials, for example