IoTnet Pilot

Why an IoTnet pilot?

The Internet of Things (IoT) enables researchers and students to easily collect data for research or projects. IoT sensors are also used to make buildings more efficient, sustainable and comfortable.

All these IoT devices need a connection to a network, but the Wi-Fi network is not suitable for this. Many sensors also use a separate low-power network, which is suitable for battery-powered sensors. We started this IoTnet pilot to support the growing demand for a tailored connection for IoT devices.

What is IoTnet?

More and more smart devices and sensors are using networks other than traditional ones such as Wi-Fi and 4G/5G. An IoT network is well suited to this. The characteristics of such a network are: 

• Large scale: Capable of connecting billions of devices, from smart thermostats to industrial sensors and self-driving vehicles.
   
• Low speeds: As many IoT devices mainly transmit simple data, such as measurement data, they do not require high speeds.
   
• Energy efficiency: Optimised for devices with limited power supply, such as battery-powered sensors.
   
• Security: Requires robust protection for the many connected devices and data streams to ensure privacy and security.

With IoTnet, SURF is implementing such an IoT network, initially focused on LoRaWAN. It is possible that other protocols may also be supported in the future. 

All devices have their specific connection

IoTnet operates with low bandwidth and low energy consumption. It is specifically designed for connecting wireless low-power devices. Wi-Fi devices have different technical requirements for connecting to the network, which are provided by SURFwireless. This service is fully tailored to the needs of wired devices. The right mix of these technologies ensures that all devices are connected in the most efficient way possible.

How does IoTnet work?

IoTnet consists of the following components:

1. IoT-gateways on site at institutions. These collect the sensor data and send it to the central environment, based on open-source software.
2. The central environment, the so-called IoT network server at SURF. There, the IoT devices are registered in a web interface and it is determined where the generated data is sent for processing.  

LoRaWAN technology

We work with IoT gateways based on LoRaWAN technology. To achieve good LoRaWAN coverage, so-called LoRaWAN gateways are installed. For larger buildings, clusters of buildings or campuses, outdoor gateways are also placed on the roof. This also allows a large part of the coverage to be achieved inside the buildings. We closely follow technical developments. If other technologies besides LoRaWAN become relevant, we can add them to IoTnet.

What are we testing in the pilot phase?

In the pilot phase, we are testing the experiences of institutions from various sectors with IoTnet. We are curious to find out how useful the service is perceived to be and how it scales when applied on a large scale. For the future roll-out of IoTnet, we want to investigate how this can best be approached and how we can set up monitoring and management effectively.

IoTnet is a solution to 3 challenges:  

1. Suppliers, researchers, and teachers are currently developing their own solutions for connecting devices to a network. This is resulting in too many different IoT infrastructures. IoTnet ensures that IoT connectivity is centrally available, an open infrastructure specifically for wireless low-power devices. Users can always get started quickly and easily. 
    
2. The lack of specialist knowledge about IoT networks in IT departments. By offering IoTnet, IoT knowledge is brought together at SURF, and all institutions can make use of it.
    
3. No insight into data flows at external suppliers. With IoTnet, we can keep data from IoT devices within our own controlled SURF network, monitor it ourselves, and decide where it goes. 

This is what IoTnet can do on and around campus: 

IoTnet enables the creation of smart buildings on campus through:

• Monitoring room occupancy. 
• Monitoring the utilisation of rooms and buildings.
• Monitoring emergency lighting.
• Measuring and controlling the indoor climate on that basis.
• Providing insight into energy consumption and possible savings options. 
• Predictive maintenance (PdM) using IoT sensors, AI and machine learning to analyse real-time equipment data such as vibrations, temperature and acoustics to predict malfunctions before they occur. 
• Monitoring and sharing available parking spaces. 

Specific applications and inspiring examples can be found here
 

Future scenario 

The aim is to include IoTnet in the basic fee and roll it out collectively at all institutions affiliated with SURF. In this way, we offer a cost-efficient IoT network for education and research in the Netherlands.