The idea is simple: Countless chips with sensors are placed in/on buildings, cities, clothing, farm animals and even people, and telecommunications technology is connecting precisely these chips/sensors to establish the “Internet” of things. The “connected” objects can provide data via status parameters (e.g. into the cloud), on the one hand, and these “connected” objects can be controlled via an app or similar devices, on the other hand. For example, microchipped clothing can pass on care instructions to a washing machine, a heating system can be remotely regulated via app, or sensors in machines provide the relevant data for predictive maintenance.
The Internet of Things is made possible above all by the dramatic price decrease for computer chips, storage capacity, sensors and connectivity (telecommunications). Take data storage, for example: Whereas in 1965 the storage of one megabyte of data still cost USD 85,000 (adjusted for inflation), today these costs are only USD 0.00002 (sic!).
The use cases are virtually endless, and expectations of the economic significance of the Internet of Thing are correspondingly high. Forecasts by different institutions show a high variability, but here’s a few figures to give you a rough idea: The consultancy McKinsey estimates the economic added value (cost savings, new business models) at about 11 trillion US dollars annually by 2025, while the chip company Arm forecasts about 1 trillion connected devices by 2035.
The Smart Home is already reality. Room temperature can be set via Smartphone App, you can turn up the heating remotely just before leaving the office (with significant potential for energy savings). The door lock can be opened with a electronic key using a smartphone (you always have it with you anyway, so you save the key). Of course, you can also open the door for visitors via smartphone as soon as they have been identified by the camera on the front door.
The lighting in the Smart Home can be controlled by voice command, however, you can also go for automatic regulation depending on the daylight. Blinds can also be controlled by voice command. Robotic vacuum cleaners are already being used in millions of households. You may also be interested in mattresses with sensors that measure the heart rhythm and monitor sleep behavior.
As is well known, the refrigerator, which triggers automatic reorders, turned out to be a flop. But what is being considered useful, on the other hand, are refrigerators with camera: Their contents can be easily accessed via app while shopping in the supermarket. In the kitchen, there are also apps in connection with household appliances, for example from Whirlpool, which can be used to scan barcodes of ready meals and automatically provide the oven with the necessary information for cooking.
But such a smart home is by no means “plug & play”. In an issue of the “Technology Quarterly” of The Economist, Ben Wood, head of research at the analyst firm CCS Insight, reports on his experience in setting up his smart home, which has even won a prize in 2017. The set-up took weeks rather than hours, and Ben Wood has laid about 2 kilometers of cable in his home. The “heart” of his Smart Home is a data center of a size, that you may not expect in a private home, rather in a small-sized company.
A particular challenge was the incompatibilities between products from different manufacturers; although standards do exist (Zigbee, z-wave), manufacturers still use proprietary interfaces or implement standards only partially. It was not until the end of 2019 that Amazon, Apple and Google agreed on a new open standard that is intended to simplify networking between devices in the connected home. But it will be several years before these standards actually come into effect on the smart home market: The working group (which includes IKEA and others) wants to start by defining the specifications, and present a first reference implementation by the end of 2020.
This is something users of smart home technology should be prepared for anyway: The market is currently undergoing an evolutionary process where certain technologies prevail and others do not, where certain offers are accepted by customers and others are not. In short: In the worst case, homeowners install the technology of a company that ceases operations some time later. Take Revolv (a Google-investment) as an example, which went off the market in 2016. An user hit by that insolvency wrote, “My house stops working.”
The author, journalist and futurologist Matthias Horx has implemented numerous smart home features in his “Future Evolution House” (see www.zukunftshaus.at). In his (German) book “15 ½ Rules for the Future” (German: “15 ½ Regeln für die Zukunft”) he describes his disillusionment: “In my experience increasing home automation creates a displacement feeling. One suddenly feels homeless, superfluous. An automated home is characterized by the fact that it can function autonomously. It actually does not need the human being any more (p. 124). And: “Smart Homing is in reality a feature for lonely people. For people who live alone and have too much to do to really be at home. Who are constantly on the road.” (S. 125). In short, it remains to be seen how customer acceptance evolves and how big the market for smart homes turns out to be.
In the medium and long term, the market for commercial use of IoT is bigger than the market for Consumer IoT. Building management technology is an important market. For example, sensors measure the daylight intensity and control the lighting accordingly. A company in the Siemens Group (Siemens Smart Infrastructure) also equips buildings with infrared cameras, beacon technology, temperature measurement devices and sensors for energy consumption. Based on the data generated in this way, Heat Maps can be generated that make visible which areas of the building are heavily used and which are not (underutilized). In this way, the usage/utilization of a building can be optimized.
The provider Comfy (also part of the Siemens Group) allows employees in buildings to use a smartphone app to set the desired temperature and lighting to individual requirements. The building “learns” with the help of this input/information and ensures an optimal indoor climate and lighting. Other features in preparation in the area of building management include inventory tracking, so that hospitals, for example, can efficiently determine where used equipment and medical material is available.
Insurance companies are also very interested in IoT technology, we’ve already seen the first applications in the market. The aim is to establish a precise determination of risk profiles of the insured in order to balance the insurance premium individually. In other words, policyholders can optimise their risk profile through good behavior, they will in return benefit from lower premiums. For example, some car insurance providers offer the option of installing a black box in the vehicle so that safety-relevant driving profiles can be determined based on acceleration and braking behaviour, driving behaviour in bends and the like. The British insurer Aviva ranks among the pioneers of this approach, it offers the app Aviva Drive, which evaluates driving behavior with GPS and offers lower premiums to drivers with exemplary driving behavior.
The same principle can be applied in other areas of insurance, e.g. life insurance. Let’s take the Chinese insurance company Ping An; clients of Ping An can use the facial recognition software, which determines the body fat percentage; this information is taken into account when calculating the premium for life insurance. This example underlines that IoT technology allows surveillance at an unprecedented level, which – depending on the culture and definition of privacy – may not always meet with acceptance. For example, the above-mentioned use of Beacon technology for building Management also allows the tracking of movement patterns of individual persons, by using their smartphones or building access cards. The size of the market for IoT will depend significantly on the acceptance for such monitoring associated with IoT. Studies/surveys indicate that, especially in Germany, the willingness to share personal data (e.g. in insurance contracts) for possible price advantages is quite low.
Last but not least an example from the agricultural sector. The Austrian company smaXtex has developed a sensor that is swallowed by a cow and lodges in the cow’s stomach. The sensor measures data on body temperature, movement patterns, acid levels and so on; whenever the cow passes near a data station, the data is transmitted. This data can be used to precisely determine the time of calving before birth, for example, and to identify diseases at an early stage and treat them with considerably less antibiotics.
The importance of IT security is growing in the face of a continuously increasing number of successful attacks and ever greater costs of damage. One thing is clear: In an increasingly connected world, the security risk is growing rapidly because the greater the number of connected devices, the higher the number of attack angles. You’ll find numerous reports on successful attacks on networks. You may have heard of the successful attack on a casino, which was carried out via the gateway of an aquarium that was connected to the Internet. Many will also remember the spectacular hack of a car (from Fiat Chrysler) in 2015, where a CyberSecurity company had remotely taken control of the car for the magazine Wired: the hackers could control the music system, turn off the windscreen wipers, even the engine, and – under certain conditions – take control of the steering wheel. The car company had to recall 1.4 million vehicles. The weak point was the infotainment system, which was not separated from the car control.
In 2017, the Food and Drug Administration (FDA) initiated the recall of a connected pacemaker after serious security gaps were discovered. One can simply imagine the unimaginable damage that can be caused in such scenario, for example by hacking connected insulin pumps. It should be pointed out that completely secure software is about as likely as perpetual motion machines. That is: impossible. Experience shows that a good programmer (even with good quality assurance) generates in his/her code about one bug per 2,000 lines of code (LOC). A modern vehicle has about 130,000,000 LOC – it you do the maths, a vehicle contains 65,000 bugs. Not all bugs may be safety-critical, but in the worst case a bug is the gateway for a hacker.
Finally, it should be noted that the life cycles of the objects discussed here are typically much longer than those of smartphones, for example. While there are security updates for smartphones for a period of about 5 years after product launch (the actual usage time for smartphones is hardly more than 3 years). By contrast, vehicles – just to name one example – have a significantly longer economic life. It will be a challenge of its own for car manufacturers to ensure that the necessary programmers are available to deliver the security patches throughout the product life cycle of dozens of car models.