When faced with such potentially unnecessary expenses, it’s perhaps worth considering what can be done to help locate these passengers. If and when they can be located, further consideration should be given to what additional services they could be presented with to help them make more of what the airport offers while ensuring they get to their flight in good time. While the idea of proposing location-based services is nothing new, the recent proliferation of sensors and smart devices offers huge potential for supporting new and innovative customer services. What’s required is a means of connecting the information from these, and other data-producing hardware, to location and customer information.
The Internet of Things (IoT) is, as we know, made up of physical and connected objects, all of which generate data. And with analysts predicting more than 21 billion of these objects by 2020, there will soon be a lot more data being produced. By way of illustrating its importance, the growth rates for software, services, and infrastructure designed for the IoT are predicted to exceed a CAGR of 25 percent, and some companies have already begun to set up their own organizational divisions solely dedicated to the IoT.
However, it’s worth noting that those who most influence an organization’s IoT strategy are more likely to be from an operational background than the usual IT decision-makers. Many businesses will need to develop a strategy to enable them to collect and manage the data generated by the IoT and consider that data’s benefit to the business itself. Use cases include predictive maintenance to save money and avoid unnecessary equipment failures; using smart meters to offer new services to homeowners, and delivering features to improve the safety and comfort of drivers of connected cars. Collecting and joining together data from a range of devices, including GPS, SCADA (supervisory control and data acquisition), CCTV, Wi-Fi, and fire sensors, can be used to improve passenger communication and safety on public transport systems.
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Elsewhere, IoT-enabled, non-invasive observation of patients is revolutionizing clinical trials and remote health monitoring. Some forward-thinking companies, such as Apple, have already spotted the opportunity offered by collecting such information and have created a “research kit” providing the features necessary to detect and report medical conditions to researchers. And it’s been suggested that, by 2020, one in every 100 livestock animals could be connected to the IoT to monitor the number of cows being vaccinated, for example, or being called to milking. By the same year, it’s also been predicted that the number of sensors needed to support the oil and gas industry will have tripled.
While the opportunity to support customer services and generate revenue from the IoT in this way is undeniably huge, it is still very much in the research phase for several companies. Many banks, for example, may currently be considering how this technology can be used to develop new levels of relationships with their customers, while telecom network operators are looking for the best way to develop new services that support these initiatives and revenue streams.
The IoT is already a reality for many companies, it is just called something else. Until now, it may simply have been a network made up of objects such as a smartphone, a pump sensor, or even railway signal panel number 34. Before addressing the challenge of knowing how to connect these objects to derive value comes the more fundamental challenge of identifying these objects and where they’re located. Like an organization’s customers, the objects that make up the IoT have their own unique identity and set of characteristics that help the organization to describe, organize and understand them.
Multi-domain Master Data Management (MDM) technology is an ideal means of referencing these objects and linking them to other types – of domains – of data, such as that on an organization’s customers, locations, assets, products, and employees. MDM is based on the principle of making an organization’s master data – in this case, the data generated by the various connected objects – available and accessible to all the systems and people that need it, within the organization itself and beyond.