A major theme of Day 4 was the Internet of Things (IoT) and its role in creating smart healthy cities. The IEEE IoT Technical Community defines IoT as “a self-configuring and adaptive system consisting of networks of sensors and smart objects whose purpose is to interconnect” all “things, including every day and industrial objects, in such a way as to make them intelligent, programmable and more capable of interacting with humans” [9]. IoT is made of sensors and other components that instrument and connect our version of the world made of atoms, i.e., our human body, our devices, vehicles, roads, buildings, plants, animals, etc., with a mirror digital version made of bits [10]. This enables cities and regions equipped with IoT technology to become self-aware of their environment, dynamically reconfigurable and adaptable in real- or near-real-time, and thus more resilient and better prepared in their response to adversity [11], based on changes that are continuously monitored and captured by sensors, similar to the way homeostasis operates in living beings. The context-aware networks and sensing infrastructure of smart homes and cities also facilitate the delivery of smarter health and social care services, opening up superior and safer active living opportunities that better meet the needs of the increasingly ageing populations in Europe and elsewhere around the world [12, 13].
In his plenary keynote on Day 4 [6] (Additional file 1; and also in [13]), Kamel Boulos offered a number of examples of IoT-driven services implemented by the Spanish city of Barcelona and by Sant Cugat (a suburb north of Barcelona) to improve the quality of life of the local populations and ensure a greener and more sustainable environment. However, Barcelona is not the only smart city in Europe that has deployed such services. Nice (France), Hamburg (Germany), Milton Keynes (UK) (see slide 30 in [6]) and many other cities across Europe [14, 15] already have similar programmes in place at various stages of development. The European Commission’s EIP-SCC (European Innovation Partnership on Smart Cities and Communities) runs an online marketplace where hundreds of smart city solution proposals, projects and developments from >300 European Region cities can be browsed [16].
High-speed Internet (30–100 Mbps or better)
Common to all these smart cities programmes and developments is the need for superfast Internet infrastructure, functioning as the essential connectivity backbone for all IoT traffic and services (cf. Barcelona’s 500 Km fibre network [6, 13], and in UK, the government’s investment of £146 m in cable broadband in the Highlands and Islands, Scotland [17], and similar investments in South West England). A good mobile broadband (3G/4G and soon 5G - 3rd, 4th and 5th generations) coverage is often also necessary to supplement city and region-wide cable broadband and Wi-Fi (Wireless Fidelity) hotspots and support seamless uninterrupted mobile scenarios and applications in areas with no cable broadband/Wi-Fi access (e.g., intercity highways, smart countryside and distributed cities -- see below). A balanced and efficient network bandwidth management approach is also needed, paying special attention to specialised services such as critical emergency or health applications, while at the same time applying very minimal (temporary) or preferably no throttling to online content and other services intended for ordinary Internet users.
Big data analytics
IoT sensors, including body-worn ‘quantified self’ sensors, generate big data streams. Such data are of little value without the appropriate analytics to process and make sense of them in useful ways and in a timely manner, e.g., to support making more informed decisions and/or to react or pro-act by triggering appropriate actions. Three main complementary levels of analytics are recognised. Descriptive analytics are concerned with what has happened (or is happening right now) and where it happened (or is happening). Anticipatory or predictive analytics focus on what could happen next based on past and present data, so that cities and regions can be best prepared to take appropriate action, while prescriptive analytics deal with the latter, i.e., with identifying the best course of action to take in response to an anticipated issue from among one or more available alternative options and in light of any constraints, resource availability and other factors or requirements that should be considered [18, 19]. However, in applying analytics, one (or the software algorithms used) should not go beyond the actual statistical strength of the (big) data, and should accommodate sound ‘error bars’ around all inferred predictions [20]. Also, big data methods can only be truly useful when paired with more conventional forms of information collection, or what some researchers call ‘small data’ [13]. Cities and regions should avoid being lost in a costly flood of big data, by starting with (the right) questions, not with data, and by using the right-sized data and analytics (‘big data diet’ and ‘light analytics’) to answer those questions.
Standards
IoT relies on a growing number of sub-technologies and subsystems that need to be seamlessly interconnected and interfaced with one another in real time. This can only be achieved through the adoption of adequate standards and protocols for measurement, communication, integration, interoperability and control [6, 13]. Logvinov describes five key components/requirements and the corresponding standards governing them, without which IoT and its connected ‘things’ would not exist: the need for smarter power consumption, storage and management; the need for stronger safeguards for privacy and security; high-performance microcontroller units (MCUs); sensors and actuators; and the ability to communicate [21]. Web standards are also essential to ensure that IoT open data repositories, applications and services are able to interact seamlessly wherever and whenever needed (‘data plumbing’ standards, to ensure big data flow smoothly, securely and reliably through all ‘data pipes’).
Privacy and security
IoT data and device privacy and security are among the most pressing challenges facing IoT-driven smart cities [6]. Users of connected devices and appliances such as smart TVs are often signing up to privacy and end user agreements that, besides being too long to read and understand, offer no alternative choice: if the user declines the agreements, s/he cannot use the equipment [22]. Furthermore, connected cars and body-worn or implanted medical devices can be remotely hacked, putting human lives at risk, and calling for a more security-aware approach to designing future devices and services [23, 24]. Possible solutions to IoT privacy concerns include offering individuals an option to ‘opt out’ of syncing their data with third-party or public cloud databases and services and become their own service providers [25]. The European Union recommends that IoT networks give individuals the rights to their own data and that privacy-friendly default settings be developed on IoT products and services to give users more control over what information is shared with others [26]. Rogers proposes a ‘right to introspection’, that users should be able to know exactly what and when data are leaving a device and their own home. He also recommends that manufacturers implement micro-client-side policies on IoT devices that users can control (e.g., to set bounding values such as temperature limits, so that deliberate attacks aimed at sending equipment out of limits can be prevented), as well as hardware switches to allow users to physically turn off features such as network and location functions. The latter (hardware switches) would afford a visible indication of the physical state of a connected device (with no need for a software user interface), besides enforcing a local, hardware-controlled form of security that cannot be easily overridden remotely [22].