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Wireless Applications

The Smart City Project in Santander

March 1, 2013 By: Alberto Bielsa, Libelium Sensors

The city of Santander in Spain is the site of a large-scale Smart City test bed. As part of this project, Libelium's wireless sensor networks are used to collect data on a range of parameters important for the health of the city and its inhabitants.


Wireless sensor networks help to create Smart Cities, using a distributed network of intelligent sensor nodes to measure a variety of parameters, such as noise, temperature, ambient light levels, carbon monoxide concentration, and the availability and location of parking spaces, for efficient city management. The Smart Santander project—a collaboration between companies and institutions designed as a life-size laboratory for technology—is an example of a unified vision for technology to benefit the lives of city dwellers and all citizens.

Introduction
Approximately 75% of the population of the European Union lives in urban areas. The Smart City concept as the next stage in urbanization has gained ground with policy makers, leading to investment in human and social capital, resource management, and new developments in environmental sustainability. A Smart City can be considered as an ecosystem, albeit one with highly technical components. This type of urban metabolism is an open and dynamic system that consumes, transforms, and releases materials and energy; develops and adapts to changes; and interacts with humans and other ecosystems.

Air pollution harms human health and the environment. Despite the fact that automobile and industrial emissions have decreased in recent years, air pollutant concentrations remain high and air quality problems persist. A significant proportion of Europe's population lives in areas, notably cities, where the air quality exceeds emission limits for several air pollutants that pose serious health risks: ozone, nitrogen dioxide, and particulate matter (PM). The danger is local, regional, and international because the atmospheric air currents may carry air pollution emitted in one country long distances to other locations, resulting in poor air quality there.

Environmental noise affects a large number of Europeans and the public perceives it as a major environmental problem. It can have physiological and psychological effects on people, interfering with basic activities such as sleep, rest, study, and communication.

In response to citizen demand and driven by the rising importance of three main aspects of governance, this new concept for cities is taking hold to a) offer a better quality of life, b) minimize environmental impacts, and c) reduce costs. The parking scenario involves all three factors. Throughout the world, atmospheric pollution and congested roads degrade the quality of life, resulting in lost time for drivers and wasted fuel. The European Commission estimates that economic losses due to traffic delays total €150 billion per year in Europe. The need to search for available parking spaces is a significant contributor to widespread congestion and a major cause of stress for motorists. Based on calculations in Barcelona, Spain, a million drivers spend an average of 20 minutes every day looking for a parking spot, producing 2,400 tons of carbon dioxide emissions while doing so.

The Smart Santander Project
SmartSantander, developed by companies and institutions including Telefonica I+D and the University of Cantabria, aims to design, deploy, and validate a platform composed of sensors, actuators, cameras, monitors, and communication facilities to offer useful information to citizens in Santander and its environs (Figure 1).

 

Figure 1. Smart Santander location
Figure 1. Smart Santander location

 

SmartSantander is really a city-scale experimental research facility in support of the typical applications and services required for future Smart City implementation. This facility is sufficiently large, open, and flexible to enable the SmartSantander network to associate with other experimental facilities, creating a large-scale network of real-time testing nodes in different cities within Europe or around the globe to stimulate development of new applications by a variety of users, including advanced research on Internet of Things (IoT) technologies, based on the realistic assessment of users' acceptability tests. The project envisions the deployment of 20,000 sensors in the European cities of Belgrade, Guildford, Lübeck, and Santander (12,000), incorporating a large range of technologies. Let's look at the SmartSantander project in detail.

A Solution for SmartSantander
In the SmartSantander project, Libelium has deployed a large number of Waspmote wireless sensor nodes (See sidebar "Introducing Waspmote" at the end of this article) to monitor a variety of parameters. One of the main challenges we encountered during the project was the need to develop Over-the-Air-Programming (OTAP) so that we could program all the nodes wirelessly and remotely. Libelium collaborated with the University of Cantabria to improve the OTAP system, creating a more robust network that can be upgraded at any time from any place.

The diagram in Figure 2 shows the nodes, the networks created, and their connection to the cloud.

 

Figure 2. Solution diagram
Figure 2. Solution diagram

 

In this project we deployed 1,125 Waspmotes in different locations within the city of Santander, to measure temperature, ambient light, carbon monoxide concentration, noise, and free parking spaces. The five types of sensors required to take these measurements are connected to Waspmote through the Gases Sensor Board (the carbon monoxide sensor), the Parking Sensor Board (parking), the Smart Cities Sensor Board (the noise sensor) or directly to Waspmote (the temperature and ambient light sensors) as we see in Figure 3.

 

Figure 3. Sensor connection to Waspmote is via a) the Gas Sensor Board, b) the Parking Sensor Board, and c) the Smart Cities Sensor Board
Figure 3. Sensor connection to Waspmote is via a) the Gas Sensor Board, b) the Parking Sensor Board, and c) the Smart Cities Sensor Board

 

Each Waspmote node has two radios for communicating at 2.4 GHz (except for the parking sensors). DigiMesh is the protocol used to send the environmental information between nodes or from node to node while IEEE 802.15.4 protocol is used to carry out experiments within the network. All the nodes within the SmartSantander network can be used to test new algorithms without any downtime, while citizens still receive information about their environment.

If any of the five measured parameters exceeds a certain threshold, the system network analyzes the information and any node may react by sending an alarm to the central node (the Meshlium wireless gateway, in this case). To know where a sensor is located, each Waspmote can integrate a global positioning system (GPS) receiver that delivers accurate position and time information. Libelium offers several wireless modules; their specifications are listed in the table in Figure 4.

Figure 4. The distances reached by the wireless modules, depending on protocol

Model Protocol Frequency TX power Sensitivity Range*
XBee-802.15.4 802.15.4 2.4 GHz 1 mW –92 dB 500 m
XBee-802.15.4-Pro 802.15.4 2.4 GHz 63 mW –100 dBm 7000 m
XBee-ZigBee Zigbee-Pro 2.4 GHz 2 mW –96 dBm 500 m
XBee-ZigBee-Pro Zigbee-Pro 2.4 GHz 50 mW –102 dBm 7000 m
XBee-868 RF 868 MHz 315 mW –112 dBm 40 km
XBee-900 RF 900 MHz 50 mW –100 dBm 10 km
XBee-XSC RF 900 MHz 100 mW –106 dBm 24 km

*Denotes LOS and Fresnel zone clearance with a 5 dBi dipole antenna

We can reach up to 40 km with Line of Sight (LOS) conditions using the 868 MHz module, which has a high transmission power and, combined with its low operating frequency, enables a longer transmission range. Waspmote allows accurate readings and reliable and flexible transmission with nodes placed at an average separation of 1.5 km.

The data can also be transmitted via GPRS/3G, with the GPRS/3G module acting as a secondary radio providing an alternative network connection and redundancy in mission-critical situations when a message must be received, as is the case for fire alarms. The quad-band GPRS/3G module can operate in four different frequency bands and supports any cellular connection provider, allowing it to function all over the world. The project we are describing is suitable for any country.

Deployment Process
Deployment of the wireless sensor network was carried out by IDOM and TTI Norte, two Spanish companies that specialize in telecommunications and engineering. As a first step, they conducted a coverage study to learn where to place the sensors and repeaters to maximize the area covered by the project. The coverage study divided the city into 22 different zones.

Each zone had a Meshlium wireless gateway to gather the data from the sensors (Figure 5); the number of sensors communicating with the gateway depended on the area to cover. The nodes were deployed zone by zone to create independent networks, each of which works on a different frequency channel to prevent interference from the other networks.

 

Figure 5. One zone of Santander including Meshlium and its sensor nodes
Figure 5. One zone of Santander including Meshlium and its sensor nodes

 

The sensors were calibrated to check that their measurements were accurate. After calibration they were randomly tested to pass Libelium's quality control process. Each node was placed within an IP65-rated box (Figure 6) that could then be deployed in the city. The boxes were placed on streetlights as shown in Figure 7 or on the facades of buildings to minimize the visual impact on the city. Each box is powered by the streetlight to which it is attached, connected through residual current circuit breakers and fuses to prevent electrical problems. A transformer adjusts the current and voltage to power the nodes.

 

Figure 6. A SmartSantander box that contains a noise sensor
Figure 6. A SmartSantander box that contains a noise sensor

 

 

Figure 7. A SmartSantander box placed on a street light
Figure 7. A SmartSantander box placed on a streetlight

 

Each Meshlium gateway (Figure 8) gathers data from all the sensors within its zone, stores the data in a MySQL database, and sends the information to the Internet through a 3G or Ethernet connection. Meshliums are placed on the top of buildings to maximize the area covered.

 

Figure 8. Meshliums used in the SmartSantander project
Figure 8. Meshliums used in the SmartSantander project

 

This installation allows monitoring of environmental parameters for further study and is used to generate real-time maps for its citizens to view. The SmartSantander project acts as a large-scale experimental network that allows researchers from all over the world to test different algorithms in a real environment.

Introducing Waspmote
Waspmote is Libelium's wireless sensor network platform that combines open-source hardware and a software API to connect any sensor, via any communication protocol, to any information system. Waspmote is a scalable and horizontal development platform and integrates 60 different sensor probes for services that include monitoring air quality with gas sensors (CO, CO2, and NO2); Smart Cities deployments (Smart Parking and Smart Lighting); radiation detection; security systems; and agriculture monitoring (soil moisture and solar radiation). It is modular in its approach to radio technology, with support for communication protocols such as Wi-Fi, ZigBee, 802.15.4, Bluetooth, NFC, and 3G.

For system integrators, the Waspmote Plug & Sense line of encapsulated sensor nodes or motes can simplify outdoor deployments and reduce installation time. Waspmote Plug & Sense models are preconfigured for services such as Smart Parking and Smart Agriculture and are ready to install out of the box. The motes have connectors to let you replace or add sensors without having to uninstall the mote itself, reducing maintenance costs to a minimum. For example, you can attach a noise sensor to a network equipped with CO2 sensors, extending the service and capabilities of the installed network.

One of the main characteristics of Waspmote is its low power consumption. A Waspmote node consumes 9 mA in ON mode, 62 µA in sleep mode, and 0.7 µA in hibernate mode. Waspmote sleeps most of the time to conserve battery life. After some minutes (programmable by the user), the Waspmote wakes up, takes readings from the sensors, transmits the data, and returns to sleep mode.

 

ABOUT THE AUTHOR
Alberto Bielsa is Smart Cities Key Account Manager for Libelium, Zaragoza, Spain. He can be reached at +34 976-54-74-92, a.bielsa@libelium.com.


About the Author: Alberto Bielsa