Connext 7 min

How better integration helps build Smart Cities

A look at IoT use cases in transportation, utilities, and environmental management and the integration challenges that come with it.

Erik Assink
Erik Assink
Managing Director North America
How better integration helps build Smart Cities

Smart Cities: a known concept but in reality often applied to separate use cases. With the implementation of a Smart City Framework, local governments, in collaboration with the private sector, now have the opportunity to truly integrate urban living with technology for a better outcome for citizens, municipalities and the environment.

Urbanization is a serious global challenge. As cities bulk up, so does the stress on city-governments to manage an increasing amount of sub challenges. Transit and flow of traffic, environmental management, and utility consumption, pose just a few of the daily dealings that either cause cities to be fantastic living environments or metropolitan monstrosities. With the rise of the Internet of Things (IoT) and APIs, integration technology opens a treasure chest of opportunities for municipalities to lean towards the former. 

When you talk about Smart Cities it is inevitable that you include the need for integration solutions. In this post we’ll explore some of the Smart City use cases, its challenges, and solutions, to propel legacy systems into a cloud-based or hybrid integration-based future.

IoT use cases for Smart Cities 

The use cases in Smart City design oftentimes open up a futuristic world of possibilities. One described in (comic) books or TV ads. And the reality isn’t too far behind. The Internet of Things is opening up new use cases everyday and with the advancement in APIs and interoperability, cities can truly steer towards a more integrated technological environment. One that takes better care of its citizens and climate.

Mobility and Transportation

Mobility and transportation management make up a large sum of the challenges that growing metropoles are dealing with. Megacities like the Indonesian capital Jakarta know all about this. For example Greater Jakarta counts close to 32 million inhabitants and the inner city has close to 11 million inhabitants. Every day millions of people on the outskirts commute towards the city’s central areas for work and education purposes. An enormous inflow of traffic that stresses all elements of city management. Effective integration solutions in these extreme cases aren’t just nice-to-haves, they are essential for a city’s quality of living.

Smart city solutions in transit technology are exciting because the use cases are infinite and the applications needn’t be overly complicated. 

One of the main needs in any Smart City design is to have an integrated and connected public transportation system. One where all areas of transportation provide better flow of traffic regardless of the operating system, be it busses, trains, subways, trams, or city bicycles. Imagine if all public transport touchpoints are connected. 

Meaning, citizens would have real time access to ideal commuting routes, transportation providers and traffic lights can better prepare based on ‘load’ management, and city planning can design ideal solutions based on congestion alerts data processed by traffic control centres. Smart transportation provides a fantastic sandbox case of designing with interoperability in mind, and one that can have hyperlocal test cases as well as scalable rollout plans. 

Energy & Utilities distribution

Cities swallow energy. And vast amounts of it. The logistics to supply cities with electricity and gas require large control centres that can distribute energy consumption according to daily needs. 

What if IoT sensors in homes, businesses and public spaces would be able to provide real time data to these centres? And what if in return these control centres automatically detect anomalies in patterns and can form conclusions based on correlations across multiple data sources. And what if then these very systems, through Machine Learning (ML) build algorithms that predict when to distribute energy to these areas. 

This is a very real scenario and one that can even be monetized by city-municipalities and utility providers as it opens the possibility for a more sustainable method of energy distribution.

Environmental Management

As cities grow, so does the need for sustainable development practices. Whether we are talking water management (flood analysis, water quality, drought) or waste management (waste collection services and recycling). When applying Smart City Frameworks we can design for truly sustainable cities that enhance the quality of living for people and planet.

As clean water is fast becoming the most scarce resource on our planet, and one needless to say vital for our survival, smart design around water management can help a city thrive. Think of IoT sensors that share information on water quality. Which would help us increase investments in water filtration plants or pinpoint troublesome catchment areas and redesign for optimal use. These analyses can of course be run manually, as they have for centuries, but IoT and integration technology now allows to address issues in real time which ultimately can save lives.

There are some fantastic examples that address waste management. One of them is in smart waste management systems. Sensors placed on waste bins show waste collectors exactly where they are needed and which are the optimal collection routes. Back at the waste collection plant, the waste is automatically sorted and this information can be shared to other entities who turn waste into an asset and recycle it back into society. 

The integration challenges for Smart Cities

All these examples above require open standards and open exchange of data. To achieve that, we need to look at some of the core integration challenges that Smart Cities face. In our recent whitepaper: ‘Envision Smart Cities that Work’ we identified four core challenges.

1. Volume and velocity of data

Billions of data streams coming through thousands of sensors 24 / 7. How do you handle that as a system? Furthermore, what parts of that information is useful? And what is not useful in the moment but fits into a larger pattern that can be used at a later time? Especially when it comes to legacy systems and non-scalable platforms, the volume and velocity of data poses a significant challenge.

2. Interoperability

When talking about the challenge of interoperability, let’s take the first example of smart transit. A fully integrated way of smart public transportation. We’re talking a dozen different public transport providers with each their own logging systems. We’re talking government-owned traffic control centres handling and storing their own data. And we’ve got millions of citizens with smartphones and applications that need to be updated in real time. Somehow the overall system (or a network of distributed ones) should be able to request, receive, and send the right type of information to the right user or system. 

3. Control over data flow

When looking at point 1 and 2 above, then it raises the question: who should have control over this data flow? Should it be a single entity? In the public or private domain? Or hybrid? Smart City Frameworks would need to take into account how and to whom data streams should flow and what are the security measures.

4. Integration of legacy systems

This core challenge ties into interoperability. How to extract valuable data from heterogenous legacy systems that are kept on-premise, managed by internal develop teams? The Hybrid Integration Platform could be a look in the right direction, but it would have to be incorporated in a much larger design connecting multiple legacy systems across different stakeholders.

Integration solutions for Smart City Frameworks

Whether we are talking about a fully connected public transportation system, energy distribution or waste and water management; they are each dependable on a myriad of IoT endpoints. When designing a Smart City use case there is a clear flow of data to follow.

IoT Field Sensors > Field Gateways > API Cloud Gateways > Data Lake > Data Warehouse(s)

In this basic setup the field sensors go through connected field gateways, which then enter the cloud through API gateways making their way to data lakes and eventually data warehouses where they can be interpreted, analyzed, implemented, and communicated back to systems accordingly.

Whether it is all coming to one data warehouse or multiple, the integration architecture should be Microservices-based. This decoupled method of integration makes for an agile and scalable solution. Especially when it comes to live environments where real time feedback of systems is required, speed and accuracy become a priority. To achieve this, Smart City Frameworks will need to adopt a cloud-first approach. A cloud-first setup also distributes risk and allows to place expertise in the systems most equipped to execute a particular task or request.

Supporting policymakers and stakeholders on their way to a Smart City

Smart cities and smart transit solutions require scalable integration platforms. Where – among others – Identity & Access Management, API Management, microservices architecture (MSA), and Open Standards are fully supported.

Yenlo, in collaboration with WSO2, developed Connext Platform. An Integration Platform as a Service (iPaaS) that is fully managed, hosted, and ready to be customized according to whichever IoT smart city design. It is specifically build to connect legacy systems with those that have a cloud-first, API-first approach. Reach out to us and our consultants will gladly advise, develop, or assist in your smart city solution or Smart City Framework.

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