As the legend has it, the first internet-connected device came into existence as early as 1982 due to practical needs: thirst, and the desire to avoid any extra steps. To spare themselves from climbing stairs for a disappointingly warm bottle of Coke, inventive programmers came up with a cunning solution: a Coke machine at Carnegie Mellon University was equipped with micro-switches to monitor Coke inventory and the length of time each bottle had spent in the machine (translating directly to how cold it is). Live data was transferred to the main departmental computer indicating if there was cold coke available. The information than was accessible from any computer on campus.
The name arrived decades after the first application. The term “Internet of Things” was coined by Kevin Ashton in 1999, who, inspired by a missing shade of lipstick on the store shelves, took part in the invention of trackable packaging for Procter & Gamble. As both examples show, practical problems necessitated innovative solutions to data collection paving the way to what we know as IoT. “If we had computers that knew everything there was to know about things – using data they gathered without any help from us – we would be able to track and count everything, and greatly reduce waste, loss and cost” – Ashton summed up the advantages of IoT for RFID Journal a decade after baptizing the revolutionary trend. He also emphasized that due to “limited time, attention and accuracy” people are more prone to mistakes while capturing data when compared to computers.
Let’s check back to our vending machines for a second. It seems a simple task to determine if there are enough beverages available to relieve the thirst of an officeful of people, but providing live data about it is rather time-consuming. What about all the more than 6,9 million vending machines situated in the USA or more than 3,8 million operating in Japan where approximately 980,000 of the thirst reducing equipment are owned by a single company, Coca-Cola – as indicated on the company’s website. No wonder why the soft drink giant decided to connect a third of its vending machines to the internet not only providing information on refilling and maintenance needs but monitoring consumption habits as well – as can be gleaned from the article of Internet of Business.
Moreover, there are problems that require more complex measuring methods, such as monitoring air pollution. BreezoMeter, for instance gathers data from more than 7,000 official air monitoring stations from 28 countries using additional sources including satellite measurements, meteorological and traffic monitoring. It is easy to see that gaining up-to-date, accurate data from such diverse and numerous features is humanly hardly possible.
Nonetheless, there is way more to IoT than machine-governed data collection. The copious amount of unstructured data piled up from monitoring traffic, blood pressure, air pollution, product placement (or almost anything imaginable) needs to be converted into useful information. This means that automated analysis is inevitable for everything from pattern recognition to anomaly detection, especially if terabytes of data need to be processed.
For a reliably-working application, BreezoMeter goes through more than 680 GB every hour while calculating air quality for more than 271 Million grid points. This means an hourly production of 29 GB of data, which adds up to 300,000 GB of data stored in the cloud. As a result of the analyses accurately-measured, real-time air pollution information, and forecasts are available and displayed in an easily accessible and comprehensible way.
The example of BreezoMeter sheds light upon another significant aspect of advanced IoT: different type of devices and information can be connected and combined to provide more complex insight to problems and facilitate more efficient solutions. Complex IoT systems also aid the reduction of maintenance, production and utility costs in case of smart manufacturing, while giving grounds to effective businesses decisions from product placement to price setting.
As a result, some – like Derek O´Halloran in his presentation on the 2016 IoT Solutions World Congress – believe that IoT is about to bring the fourth industrial revolution by inherently changing what we think about everything from agriculture to production, and transportation. According to Derek O´Halloran, the new era is marked by networks of autonomous vehicles, neuro-communication, distributed energy-systems, fully automated farming, and distributed manufacturing.
Being on the threshold of a revolutionary era always means obstacles to tackle, be it technological, social or legislative. One of the teething problems comes with one of its biggest advantages, connectivity. Data from numerous different sources can be collected and analyzed simultaneously to gain a way more complex picture than ever before, but devices produced by different companies might not cooperate in great harmony. Compatibility issues also originate from the “generation gap,” or in other words, version differences between gadgets, and software.
Thankfully, standardization and collaboration initiatives have already made great strides. Alliance for the Internet of Things Innovation emphasizes the importance of “discussion and alignment of strategic, cross-domain, technical themes and shared concerns across landscape activities” and the development of “recommendations and guidelines addressing those concerns.” Nevertheless, there are still doubts about the effectiveness of standardization, since it may not be able to keep up with the rapidly developing field.
A beneficial approach may be the collaboration of companies who work on predefined goals together to reach the full potential of the presently available technologies. This was one of the main themes of IoT Tech Expo in London this year, where successful collaborations were mentioned such as the voice control system of Ford developed hand in hand with Amazon. Despite this example, it was also noted that the fruitful shared work is not the exclusive privilege of corporate giants, but smaller start-ups can contribute to the common goal as well. It is also worth attention that prosperous application of the Internet of Things is not exclusively an IT responsibility. The best solutions usually result from fruitful interdisciplinary collaborations due to the diversity of expertise and insight.