Market Insight

Opportunities and challenges in the smart city device layer

April 26, 2017  | Subscribers Only

Pablo Tomasi Pablo Tomasi Senior Analyst, Smart Cities and IoT
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This insight discusses the dynamics emerging within the smart city device layer. The piece will start with a profile of Libelium, a company whose core commercial activities lay in the device layer and will further develop the discussion to analyse opportunities and challenges which feature within the device segment of the smart city value chain.

Libelium interoperability and agnostic connectivity used to secure a place in the device market

Libelium is a Spanish based company formed in 2006. The company provides modular, sensor-rich device solutions that can be integrated with third-party systems.

The company’s products support different connectivity protocols, including Wi-Fi, 3G, 4G, Bluetooth, LoRaWAN, SIGFOX, and ZigBee. Libelium’s Waspmote devices enable over-the-air software updates, a feature which is crucial in the IoT world where optimising costs and resources is one of the first priorities.

Libelium works across multiple IoT segments including, smart agriculture, environmental monitoring, smart water, and smart cities, among others, with different smart city projects launched for various applications such as, among others, smart parking, smart irrigation and air quality monitoring. As of April 2017, the company counts on more than 120 sensors already integrated into its offering.

In February 2016, in order to streamline customers’ entrance in the complex IoT world and provide a ready to deploy solution, Llibelium launched the IoT Marketplace. The marketplace is an online space offering integrated end-to-end solutions by Libelium and its partners to foster the expansion of IoT applications. The marketplace targets those customers looking for a solution ready to implement to start their journey in the smart cities or IoT world.

As Libelium focuses only on the device layer of the market, it is essential for the company to have a wide ecosystem of partners. As of April 2017, the company counted on a total of 84 partners. [...]

Selected Libelium smart city project case studies

Smart city project case study 1: Glasgow air quality control through sensorequipped vehicles

In December 2016, the city of Glasgow in Scotland equipped vehicles with sensors to measure air quality across the city. By equipping vehicles with sensors to measure air quality, the project gathered air quality data from different parts of the city without the need and the cost of deploying air quality control station throughout of the city.

The project was the result of the collaboration of multiple partners including CENSIS (the Innovation Centre for Sensor and Imaging Systems Technologies), Libelium, the University of Strathclyde, Microsoft, and CitySense.

This is an interesting case study as one of the key foundations of a smart city is optimising available assets. In this case, by attaching sensors to vehicles, the city can leverage the vehicles traditional activities to obtain air quality measurements across a wide area. By leveraging existing structures (in this case vehicles patterns) the city does not need to deploy air quality sensors across the entire city thus saving on costs and investments.

We expect that cities will increase the use of sensors and devices attached to vehicles for diverse purposes besides environmental monitoring, with possible applications including traffic mapping and analysis, road monitoring, and physical infrastructure monitoring.

The use of sensors in vehicles is not a prerogative of cities and there are examples of companies using the same idea to develop new services. For instance, in its community-based parking solution, Bosch is using sensors placed on the side of cars to send parking slot related information to the cloud where the data is analysed, thus mapping the availability of parking slots. This information is then made available for other drivers looking for a parking slot. As with other solutions, the Bosch initiative is not free of problems; for instance the system requires a high number of vehicles sending data to the central platform to provide comprehensive information and this is conditioned of having a large number of cars in the street equipped with this technology. This may take several years to happen.

Smart city project case study 2: Malaga traffic management solution

In June 2016, in the Spanish city of Malaga a research group led by the University of Málaga developed an Urban Information System (UIS) to gather all relevant information about the city environment with a particular attention on traffic data leveraging different sensors.

The UIS uses sensors to gather traffic information such as vehicle counting, vehicle identification, noise level, humidity level, and other air quality measures.

The system was developed leveraging Libelium’s hardware and software capabilities. In the project the different nodes (Bluetooth, ultrasound, laser, gases, and environmental) use ZigBee communication to transmit information to the gateway node (Meshlium gateaway). From there, the gateway sends the information to the central software through Wi-Fi or 3G technology. Thanks to the Bluetooth nodes which track Bluetooth devices, the system identifies the various Bluetooth devices and consequently the car carrying it, thus allowing for a mapping of the car’s path.

This project provides city managers with a better understanding of traffic patterns including real-time information about vehicle origin-destination patterns, thus empowering them to make more informed decision about traffic planning.

Our analysis

The evolution of the device segment, interoperability and agnostic products as core attributes of the layer

Major opportunities in the segment, are the increasing number of devices to be used in smart city projects, cities’ thinking about efficiency and optimisation, and the expanding role of edge computing devices.

Connected device shipments in smart cities will increase significantly in the coming years as the increasing number and size of projects will foster the growth. According to IHS Markit data global smart city device shipment will reach 1.4 billion by 2026. Asia Pacific will be a key market with around 50% of smart city device shipments. Regarding vertical applications categories, physical infrastructure will have the largest share with more than 900 million smart city device shipments. Mobility and transport will also be a key segment with more than 300 million shipments. [...]

An agnostic approach in regards to connectivity protocols and applications is essential in a market that is fragmented and developing with multiple alternatives competing in the market. Supporting different protocols can help cities which can use the device without the need to worry about the type of connectivity that is deployed for the specific project.

In this case, as Libelium focuses on the horizontal layer of devices and sensors there are extensive opportunities for companies active in the other layers of the market to partner with it given their respective strengths and expertise. (For further information about the smart city ecosystem and players please consult IHS Markit Smart City IoT Ecosystem and Value Chain Report). [...]

Market trend: the expansion of edge computing in smart cities

Libelium’s devices stay at the edge of the system and send the data which is collected through multiple sensors towards the cloud platform or software layer where the data is analysed. The opportunity for companies in the device segment is to continue exploring the growing trend of edge devices. With more and more data being generated within smart cities the role of edge analytics will increase in importance as edge computing provides a first analysis of the data gathered before sending only relevant data and information to the central system. [...]

A primary use case for edge computing is for those applications whose data require high bandwidth. In the case of smart cities, safety and security and mobility and transport applications which may rely on cameras to generate data are a prime example of how edge computing could be an optimal fit. Camera generated footage which can also be in HD format requires high bandwidth to be transmitted and this can negatively impact the network. [...]

Obstacles in the device layer

One of the major obstacles to be found in the device layer is in the possible commoditisation of the device itself as the wider IoT movement is pushing a transformation in companies’ business models from a product-based model into a service-based one. Such a scenario would reduce the device-maker relevance within the wider smart city project value chain and this would affect its revenue generation as well as its ability to invest in R&D to play a larger role within the ecosystem. For this reason creating a business model that goes beyond the single product purchase is an essential step as by providing a service, the device maker will strengthen its position in the ecosystem. [...]

 

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