Functional IoT from the Consumer’s Perspective
The single largest difference between this technology and most others that have come before – along with the requisite hype, news coverage, discussion and confusion – is that almost without exception the user won’t have to do anything to participate in this ‘new world’ of IoT. All previous major technical innovations have required either purchasing a new gadget, or making some active, conscious choice to participate in some way. Examples include getting a smartphone, a computer, a digital camera, a CD player, etc. Even if sometimes the user makes an implicit choice to embrace a new technology (such as a digital camera instead of a film camera) there is still an explicit act of bringing this different thing into their lives.
With IoT, almost every interaction with this ecosystem will be passive – i.e. will not involve conscious choice by the consumer. While the effects and benefits of the IoT technology will directly affect the user, and in many cases will be part of other interactions with the technosphere (home automation, autonomous cars, smartphone apps, etc.) the IoT aspect is in the background. The various sensors, actuators and network intelligence that makes all this work may never directly be part of a user’s awareness. The fabric of one’s daily life simply will become more responsive, more intelligent and more contextually aware.
During the adoption phase, where the intelligence, interaction and accuracy of both sensor, actuator and software interpretation of the data is maturing we can expect hiccups. Some of these will be laughable, some frustrating – and some downright dangerous. Good controls, security and common sense will need to prevail to ensure that this new technology is implemented correctly. Real-time location information can be reassuring to a parent whose young children are walking to school – and yet if that data is not protected or is hacked, can provide information to others that may have far darker intentions in mind. We will collectively experience ‘double-booked’ parking spaces (where smart parking technology gets it wrong sometimes), refrigerators that order vodka instead of milk when the product tracking goes haywire and so on. The challenge will be that the consumer will have far less knowledge, or information, about what went wrong and who to contact to sort it out.
When your weather app is consistently wrong, you can contact the app vendor, or if the data itself is wrong, the app maker can approach the weather data provider service. When a liter of vodka shows up in your shopping delivery instead of a liter of milk, is it the sensor in the fridge, the data transmission, an incorrectly coded tag on the last liter of milk consumed, the backoffice software in the data collection center, the picking algorithm in the online shopping store… the number of possible areas of malfunction are simply enormous in the IoT universe and a considerable effort will be required to ascertain where the root cause of failure is with each error.
A big part of a successful rollout of IoT will be a very sophisticated fault analysis layer that extends across the entire ecosystem. This again is a reason why the network of IoT itself must be so intelligent for things to work correctly. In order for data to be believed by upstream analysis and correctly integrated into a knowledge-based ecosystem, and for correct actions to be taken a high degree of contextual awareness and ‘range of acceptable data/outcomes’ must be built in to the overall network of IoT. When anomalies show up, the fault detection layer must intervene. Over time, the heuristic learning capability of many network elements may be able to actually correct for the bad data but at least data that is suspect must be flagged and not blindly acted upon.
A big deal was recently made over the next incarnation of Siri (Viv) managing to correctly order and deliver a pizza via voice recognition technology and AI (Artificial Intelligence). This type of interaction will fast become the norm in an IoT-enabled universe. Not all of the perceived functionality will be purely IoT – in many cases the data that IoT can provide will supplement other more traditional data inputs (voice, keyboard, thumbpress, fingerswipes, etc.). The combined data, along with a wealth of contextual knowledge (location, time of day, temperature, etc) and sophisticated algorithms, AI computation and the capability of low-latency ultra-high-speed networks and compute nodes will all work together to manifest the desired outcome of an apparently smart surrounding.
The Parallel Universes of IoT Communities
As the IoT technology rolls out during the next few years, different cultures and countries with different priorities and capabilities will implement these devices and networks in various ways. While the sophistication of a hyperfunctional BMW autonomous car driving you to a shop, finding and parking all without any human intervention may be the experience of a user in Munich, a farmer in rural Asia may use a low complexity app on their smartphone to read the data in some small sensors in local wells to determine that heavy metals have not polluted the water. If in fact the water is not up to standards, the app may then (with a very low bandwidth burst of data) inform the regional network that attention is required, and discover where nearby suitable drinking water is available.
Over time, the data collected by individual communities will aggregate and provide a continual improvement of knowledge of environment, migration of humans and animals, overall health patterns and many other data points that today often must be proactively gathered by human volunteers. It will take time, and continual work on data grooming, but the quantity and quality of profoundly useful data will increase many-fold during the next decade.
One area of critical usefulness where IoT, along with AI and considerable cleverness in data mining and analysis, can potentially save many lives and economic costs is in the detection and early reaction to medical pandemics. As we have recently seen with bird flu, Ebola and other diseases, the rapid transportation systems along with delayed incubation times can post a considerable risk for large groups of humanity. Since (in theory) all airline travel, and much train/boat travel is identifiable and trackable, the transmission vectors of potential carriers could be quickly analyzed if localized data in a particular area began to suggest a medical threat. The early signs of trouble are often in areas of low data awareness and generation (bird and chicken deaths in rural areas in Asia for example) – but as IoT brings an improvement in overall contextual awareness of environment initially unrelated occurrences can be monitored.
The importance and viability of the IoT market in developing economies cannot be underestimated: several major firms that specialize in such predictions (Morgan Stanley, Forbes, Gartner, etc.) predict that roughly a third of all sales in the IoT sector will come from emerging economies. The ‘perfect storm’ of relatively low-cost devices, the continual increase in wireless connectivity and the proliferation of relatively inexpensive but powerful compute nodes (smartphones, intelligent network nodes, etc.) can easily be implemented in areas that just five years ago were thought impenetrable by modern technology.
The next section of this post “IoT from the Business Point of View” may be found here.
Parasam 