Part 2: From Smart to Brilliant: Connected Devices and the Internet of Things
Modern day devices are bringing about a sea change in the way the world interacts. The “Internet of Things” has become the meta concept of the hour in the software development world, following closely on the heels of conceptual predecessors like Web 2.0, Mobile First, and Big Data.
In many ways, the “Internet of Things” represents the intersection and evolution of each of these concepts. It promises to provide improvements to the world around us by digesting vast amounts of data from mobile devices and other connected devices.
There is a whole set of activities that need to be taken care of to get to the point where devices can go from smart to brilliant. Some of these include:
- Existing sources of data need to be tightly integrated into a system that allows easy access from remote computing devices and increased intelligence at the sensor itself.
- There is an urgent need to set up dedicated mobile-to-mobile (M2M) networks for communicating raw data and/or results of local processing of data. This collective network of devices will help increase coverage and the amount of discrete localized data available for aggregation.
- Individualized smart sensors can be deployed to help expedite decisions. Machine learning and AI advances will allow machines that learn to make decisions unguided by users but using pre-defined rule set/criteria.
How can things be made smarter?
The answer to this pertinent question lies with sensing environmental conditions and the operational state of machinery (automotive, home, personal devices, etc.). Products must be able to use that data to guide intelligence across a system and to guide actions of services and messaging to the users. With enough sensors and data being collected, an objective data-oriented interpretation about individual users and groups of users can be developed. How can the machines be made sufficiently intelligent to improve the quality of life for the user and create a dent in the universe?
The more we know about the micro issues the more we can influence outcomes and achieve meaningful results. Predictive algorithms, for example, can be used to guide preventative and/or restorative efforts. Today, a granular grid can be used to differentiate (over time) good from bad. These perceptions about the good and bad are bound to change over time.
The sensor-based health monitoring platform we designed and developed for WellAware is one example of a product that uses predictive algorithms to make the world a better place. The WellAware solution uses non-invasive technology, data analytics, and proprietary algorithms to provide objective information to caregivers that empowers them to make proactive decisions about care before emergent conditions become acute.
Smart devices have been around for a long time now. So why is the “Internet of Things” just now becoming possible? It’s partly due to the reduced cost of components and continued advances in microelectromechanical systems (MEMS), which have enabled new form factors and packaging of electronics to increase intelligence at the device level. Single board computers with a variety of interfaces are becoming less expensive and available at an ever increasing rate. In addition to supporting the continuing improvement of devices and making them smarter, these computers are also capturing the (very early) interest of the next generation of engineers and inventors who are learning how to make things talk and how to write software to facilitate the conversation and create tangible value.
These smart devices collect a finite/established set of data that can either be acted on locally by a user (or the device) or communicated to another device or system capable of performing advanced calculations and looking beyond the micro environment to solve larger problems.
The cause and effect at each level of aggregation and intelligence is fundamental to extracting value and solving problems with smart devices and systems.
There is no denying that the availability of Radio Frequency (RF) interfaces and wireless data interfaces fueled by the proliferation of mobile phone networks and the emerging dedicated M2M networks will extend the range of current devices. This will add richness of data to systems employing machine learning and artificial intelligence to influence decisions and further automate our day-to-day life.
These devices and systems per se can’t be smart without good software and good user experience design. Smarter devices will influence how users interact with the technology around them. Voice and gesture-based interfaces are both examples of sensor-based user interfaces that are gaining in popularity with consumers and will become commonplace in the next few years. The ubiquitous nature of smart devices, coupled with human nature, dictate that aesthetics and ergonomics play a prominent role in the design process.
In the next and final piece in this series, we will look at verticals and industries that are most likely to be revolutionized by connected devices and the “Internet of Things.”