Why smarter cities need smarter solution ecosystems

When I started a decade ago to become interested in Internet of Things (IoT) and what it can do to improve the life of communities and cities, IoT technology was still at its infancy. Available connectivity technologies were ill suited for simplified deployment of IoT infrastructure in cites and the IoT end device ecosystem was very fragmented and nascent, riddled with protocol and hardware design flaws.

Due to resulting costs and complexity, only the larger cities such as Amsterdam, Barcelona, Copenhagen or London could carry out technology pilots to explore how IoT and other digital technologies could enable a more sustainable running of a city and improved quality of life for its residents.

These explorations were often enabled by grant funding which only larger cities were able to win or were bank rolled by deep pockets of tech giants such as CISCO, Intel and IBM who were looking to create a shiny reference customer for an emerging lucrative market opportunity. I was personally involved in such initiatives at Intel Labs working with cities such as London and Dublin to demonstrate the benefits of “vendor powered” IoT solutions in cities.

Fast forward one decade the situation has drastically changed on the ground. New IoT solution ecosystems have emerged, enabled primarily by new forms of IoT connectivity technologies such as low power wide area networks. 

These technology advancements fundamentally change both affordability and accessibility of smart cities solutions and are democratising how cities can experiment with IoT use cases that work best for them.

Cities can now deploy their own IoT network infrastructure and enable simple connectivity across their communities and wider regions without significant infrastructure investments. For example, a city wide LoRaWAN network is cheaper and easier to setup than a city-wide WiFi network and a fraction of the cost of a cellular network variant. In addition, IoT devices and end-to-end solutions have become considerably more affordable, and a rich variety of standards compliant solutions have emerged from different vendors on the market.

Larger UK cities such as London, Leeds or Manchester are now joined by local authorities such as Norkfolk, Berkshire and Surrey who are able to make comparably modest investments in LoRaWAN networks and are innovating at pace with different IoT use cases enabled on top of these. A great example is the IoT Innovation Network in Norfolk and Suffolk, which the local authorities have opened to innovate with local business to support the development of smart solutions that address local challenges and needs.

With so much recent optimism and a simplified and more reliable IoT technology ecosystem, the question remains; what is holding back the IoT boom in cities across the world?

In the remainder of this article, I explore current challenges in emerging IoT solution ecosystems for cities and what needs to be done to significantly remove adoption barriers for cities.

Solution Silos

Despite the emergence of a richer IoT device ecosystem around specific IoT connectivity standards such as LoRaWAN, Sigfox or NB-IoT the solution landscape is still very fragmented.

IoT solutions are end-to-end systems that consist of IoT devices, network infrastructure, cloud-based data and application enablement platforms, and ultimately service dashboards that provide insights and decision support to human users.

Some solution providers build the entire value chain themselves creating their bespoke IoT devices, data platforms and service dashboards from scratch. Others act more as system integrators and rely upon off-the-shelf IoT devices and IoT platforms from third parties to create more tailored smart city service offerings. There are even those who deliver a hybrid offering; for example, developing their own devices but making use of third party IoT platforms etc.

These solutions are often vertically integrated and serve a specific application and service. A city that choses to procure a set of solutions over time such as smart parking infrastructure, footfall counters, air quality monitors, and smart waste solutions is very likely to end up with four different solution stacks, supported by different network technologies, cloud platforms and dashboards. The figure below illustrates this in more detail.

Vertically integrated solution stacks of different smart city applications.

As a result, a city may lose considerable synergies that might be possible via a more integrated technology stack.

 Different services and dashboards may vary in usability and user experience. This might not necessarily be an issue if the end users of these systems are different, but it makes it nevertheless complicated to provide a combined view over what is happening in the city.

Secondly the duplication of functionalities across the stack leads to a city paying for the same functionality multiple times as they procure every solution independently. This applies specifically to connectivity and cloud resources which may often be interchangeable (subject to some specific use case constraints). A city that has invested in its own connectivity infrastructure or has a preferential agreement with a cloud/application vendor can benefit from more integration across the solution stacks.

An alternative approach to this scenario is for a city to establish a common connectivity and application enablement infrastructure (referred to as the urban service platform) and incrementally procure solutions that build upon it. While the benefits and resource savings are obvious through the infrastructure reuse and alignment, the solution ecosystem on the market is not prepared for this currently. 

Reusing a common network and application platform stack for multiple urban IoT services.

Most of today’s cities are unable to build those services inhouse around a common network and service platform. The solution vendors on the market have created their own vertical solutions, as they cannot rely upon a city providing all intermediary infrastructure.

Mandating solution providers to integrate their solutions around an established urban service platform and network that the city owns would result in considerable solution re-engineering that would likely defeat the cost savings that were expected from the initially foreseen integration. Also, service level guarantees are difficult to manage if the service providers rely on a significant part of the service infrastructure outside their control. The use of well-defined and accepted standards for such urban platforms together with service level agreements may be able to move the market further along to this vision, but they do not represent a clear option in the shorter term.

There are also limitations in what use cases a network technology could enable. For example, while a LoRaWAN network is well suited to use cases where the data volume is low and updates are infrequent from the sensing infrastructure, it might be prohibitive in cases where higher data rates or frequent updates are needed.

From the above discussion it is apparent that full integration of the solution stack might not be practical or feasible or lead to the expected synergies. However, there are other approaches for a city to consider.

Potential synergies at the data level

A key ingredient for many smart city services that rely upon IoT infrastructure is the data those devices generate. IoT data captures information about real world systems and processes. It feeds customised service logic, algorithms, or dashboards to optimise the operation of the service, deliver better service user experience, and generate insights needed for smarter decision making and decision support for respective service users.

Most existing vertical IoT solutions on the market hard-wire this IoT data to their value-adding algorithms, end user applications and dashboards. The data is locked into the often-proprietary vendor solution stack. While this setup works well to satisfy the initially envisioned service need, it prevents greater synergies to occur from the reuse of the generated IoT data. 

Let’s explore the concept of IoT data reuse in more detail.

IoT data can provide value beyond the initial provisioned service, if it can be effectively re-used for other innovation. Let’s take the simple example of an air quality monitoring solution that has been deployed in a city. The initial service provides a citizen facing dashboard on the city website that can be consulted by citizens. Data is captured in the vendor’s system and the only way of accessing the information is via the provisioned web site widget that displays the current (and possibly historic) air quality readings as an easy-to-understand air quality index. The mayor and the citizens can see the air quality index across the city, seek reassurance or take appropriate actions on a bad day. That’s the end of it.

If the mayor wants this data stream to be integrated with a dashboard that pulls together other real time city KPIs, he needs to speak to the original solution vendor. The solution vendor might be willing to adapt their widget to suit the new dashboard need but will charge the city for it again.

If, however the collected air quality data is made accessible via APIs to third parties, much more value could be created. Scientists at the local university could pull in the raw underlying air quality readings and create a more accurate air quality forecast model instead of relying on a computed air quality index. Data could be easily integrated into an enhanced mayor dashboard without involvement of the original system supplier. A business who provides a multi-modal travel app could make their route planning engine suddenly air quality aware. Local schools could offer an alerting app that would notify students with allergy or asthma of increased pollen or pollution levels before leaving their home in the mornings. And the list goes. All this could be enabled by the same IoT infrastructure deployment without additional costs.

Another benefit from sharing data across different solution silos and making it accessible is that valuable insights could be generated that are currently hard to obtain from data of a single solution. For example, availability data from an electric vehicle charge point network are currently not accurate enough to determine the real availability of a charging bay, as only connected cars that are actively charging are being detected. A non-EV could be parked on the charging bay, rendering the space unavailable for an EV driver. Current systems however would mistakenly show this spot as available to the great inconvenience of EV drivers desperate for some charge. Combining data from EV charge point infrastructure with data from a parking sensor deployed at the charging bays would improve reliability significantly, but requires exposure of both data streams alongside another.

Unlocking IoT data from vendor silos

The example above demonstrates the value that effective data sharing and reuse could enable for a specific IoT solution silo. While there is no network or data infrastructure reuse at the time of the solution installation, the reuse of IoT data for subsequent activities and innovation can significantly increase the value of the initial investment.

For a city to benefit from IoT data sharing, it needs to have access to the IoT data from a deployed IoT solution, ideally in a programmatic way via APIs. This will ensure that from a solution silo data can be unlocked and can be more easily reused for other current and future use cases.

A suitable strategy is to consider this case already at procurement time of an IoT solution, by mandating clear data ownership transfer from the solution provider to the city and the provision of an API to enable access to all related IoT service data. Moreover, in order to make subsequent data re-use more effective, a city could even prescribe the API to follow a specific standard and data models. This approach is taken by an alliance of more than 160 cities where specific minimum interoperability mechanisms are expected to be adopted by solution vendors. I will cover more technical details about APIs and IoT data standards in a separate blog in the coming weeks.

The benefits from IoT data sharing can be extended to any kind of IoT solution deployment. Whether it is foot fall counting on the highstreet or roadside traffic counting, data from electric vehicle charge points or smart parking lots, noise pollution from construction sites or local river levels, data sharing from solution silos provides an immediate potential for cities to enable the creation of future value. The latter is only limited by the imagination of local stakeholders and citizens and the rapidly growing global data-driven innovation community.