For example, connected cars have sufficient power and processing capabilities to include advanced functionalities such as machine learning; they come fully equipped with interactive consoles and sensors that provide real-time insights about weather, traffic conditions, and navigation routes. Most connected cars also allow stand-alone connectivity to link directly to mobile networks. This exemplifies how a shared resource—in this case, the connected car—can create a new business model to coexist with smartphones.
This model may also extend to enterprises or enable the next generation in the shared economy. Physical distance to WPDs can complicate the process of converting data to insights. Navigating mobile networks and home broadband, while taking care of differing operating system standards, presents challenges to interconnectivity and intelligence.
Remotely managing a large number of connected devices and concurrent sessions is an even more daunting hurdle to personalizing technology. The leading contenders for the technology hub role: artificial intelligence AI and mixed reality interfaces, both of which may be in a position to disrupt existing screen-based systems. Growing consumer interest in alternate interaction technologies such as virtual reality and augmented reality sets the foundation for a system that is more powerful and interactive than the modern smartphone, particularly in visually limiting situations, including driving and cooking.
The recent rise of mixed reality XR as a novel medium for interactivity also presents a potential alternative to smartphones. XR uses the combination of augmented reality, virtual reality, headsets, and holographic images to merge real and virtual worlds, enabling a user to freely interact with physical and virtual elements in real time.
XR advocates believe smartphones may become redundant if XR voice-activation commands can call up holographic screens blended with the real world, augmenting visual reality with real-time information.
The volume and density of personalized data that smartphones can capture, analyze, and synthesize is both technologically daunting and overwhelming. Wi-Fi and Bluetooth allow smartphones to interconnect with diverse WPDs; meanwhile, mobile applications have the intelligence to connect, tune, and capture information from other devices; and, finally, technology developers are working diligently to enhance identity-related features through cognitive computing and other advanced methods.
New technologies to enhance interconnectivity are continually emerging as well. These higher speeds facilitate geotagging combined with secure authorization to obtain WPD locations more quickly and accurately via a larger number of cells and automatic syncing with specific environments based on permissions. Faster speeds also improve interoperability and backhaul continuity versus discrete short-range connectivity standards such as Wi-Fi, BLE, Z-wave, and ZigBee.
Next-generation mobile networks such as 5G will potentially have the capability to provide data speeds of up to 20 Gbps, 20 times faster than 4G. Developers are rapidly bringing forth open-source applications and architecture to connect with a smartphone hub.
Technology players that work with smartphones are in a unique perch for big-data analytics: They can capture, analyze, and synthesize valuable data from WPDs to generate insights to help consumers and enterprises make actionable choices in business, lifestyle, health, and security.
Some strategies for these players include:. Initially focused on smartwatches, Google is expanding to a wide range of body-fitting devices. Android Wear enables developers to build applications for smaller screens, 27 enabling new forms of voice interactions 28 and tapping into cellular connectivity for cloud services by interacting with larger devices such as smartphones and tablets. Core services include Weave, which helps devices to securely connect and seamlessly communicate across a network, and the developer kit accelerates third-party development and creation of customized applications on the platform.
Intelligent technologies and designs have expanded to wearables, transportation, and home control. Apple Inc. Identity is designed to provide secure authorization and access for consumers to set their preferences and personalize their experiences. Ideally, identity applications should be built on learning algorithms that become more sophisticated and context-sensitive with time and experience.
In line with concerns about potential IoT-related data breaches, 36 protecting identity-related information and preferences is a top security priority. Looking to thwart intrusion and attacks, smartphone-related players are already focused on enhancing security by using multifactor authentication, advanced encryption, and biometric features to build proactive counterdefense and self-healing capabilities in both home and work environments.
Atlas is an example of an application that uses a machine learning algorithm to make decisions for consumers; it combines a traditional fitness band and intelligence platform, powered by the Motion Genome Project database of movements, with learning algorithms that automatically classify exercise routines in 3D vectors. Processing information directly on a smartphone offers the benefit of running deep learning applications more rapidly in specific situations.
One key to consider is making power-efficient smartphone-ready AI processors. For some players, there are advantages in the second architecture, or to a stripped-down handset that would be one of many connected devices dependent on the cloud for storage and intelligence.
For companies with successful business models focused on the smartphone, leaders will aim to invest in the first architecture: having stand-alone interconnectivity, intelligence, and identity. The questions, then, are how to hedge investments and how many resources should be allocated to such hedges. Interconnectivity: Does the smartphone act as a hub for other short-range WPDs, or do most devices have their own network connections?
Intelligence: Does the smartphone handle the bulk of the processing and storage for the devices and act as a gateway to any additional cloud-based resources, or do individual devices have a mix of local and cloud-based storage and processing? Interestingly, however, nearly every player would like to see more devices that follow the first architecture—having stand-alone interconnectivity, intelligence, and identity. The exception might be mobile OS providers, especially where they lack a closed ecosystem to protect their devices.
Until ecosystem players make the above strategic choices and test the benefits of stand-alone architecture and new technologies such as VR and XR , smartphones are uniquely suited to serve as an interconnector, intelligent interface, and identity validator for consumers and enterprise customers alike.
That said, in a fast-changing world of technology, companies currently invested in smartphones—building them, selling them, developing apps, handling communication linkages, working on security, etc. An independent research firm fields the survey, based on an online poll of consumers, with responses weighted to reflect the US population based on Census data. The survey offers insights into US consumer habits, wants, and trends, with a focus on smartphones and wearable and proximity devices and services.
All data is weighted back to the most recent US Census to give a representative view of what consumers are doing. The survey offered insights into consumer trends related to product and device ownership and value, mobile app usage, and advertising insights.
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