Headline image for Behind the Scenes of Connected Hull

Behind the Scenes of Connected Hull

Connected Hull has delivered workshops across the city that have engaged people of all ages discovering the advantages of collecting and sharing remote data, but how does the technology behind it work?

The project is built on top of the Things Network, a global movement that democratises data connectivity and makes it possible for communities to deploy their own radio networks.

The Things Network uses LoRaWAN technology; an emerging radio protocol that has a number of unique advantages over existing solutions.

slide explaining how lorawan works with low power and radio

LoRaWAN is low power, license exempt (meaning it is free to use) and has a long range (16km).

The geography of Hull is largely flat so we were able to install just a few base stations that would receive LoRaWAN messages and forward them onto the Things Network servers, which in turn forward the data onto our Connected Hull server. The data is stored in a database for the Connected Hull servers, before it is displayed as graphs and tables.

Users can view the data in the website or access it programmatically via a json api to incorporate in their own application. Alternatively, users can connect directly to the Things Network servers and have the data forwarded onto them if they are technically confident.

slide explaining how connected hull project works via hardware and the things network

We built gateways based on Raspberry Pi, with a custom PCB to link with the LoRaWAN interface.

hardware components used include raspberry pi to build a gateway for connected hull

The design is available from our project’s GitHub site here.

The goal of Connected Hull was to be inclusive, and by adopting this modular architecture it makes it possible for anyone to make a start by receiving data, while still permitting advanced uses to get access to the raw data.

This approach was also taken when providing facilities for programming the devices that would be in the field collecting data.

example of code using drag and drop functionality to collect data from a sensor node

The devices can be programmed in Python or via drag and drop blocks. Also, by providing access to other people’s projects, new users can explore already working code and then adapt and remix the code for their own applications.

Header image by Jerome Whittingham

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Headline image for Congratulations to Hull's latest Digital Pioneers!

Congratulations to Hull's latest Digital Pioneers!

The project submitted by the 'Sunscreen Superstars' team at our recent Ada Lovelace Day has received a special recognition award from the judges of the Pioneers Challenge.


Congratulations to the group and we look forward to hearing more digital making tales on their return from the Pioneers Summer Camp at Google HQ next week.

The KS3 students designed a project with a purpose to protect peers from harmful sunlight. The young digital makers measured UV levels and processed the data to display warning lights when it was time to apply more suncream.

Their code has already been remixed and has inspired others to make inventions that help make the world better. The project shows that computing has applications in the outdoors and is not just confined to the classroom.

Example project using a strip of LEDs to show data collected for UV levels attached to a bottle of suncream

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Headline image for Winning Data: Taking data-driven driving decisions with IOT

Winning Data: Taking data-driven driving decisions with IOT

Project Blyth, part of the Greenpower Education Trust initiative, sees young people building and racing their own electric cars. Since all the cars have the same power source, the difference between winning and losing is dependent on making improvements to the car’s design and driving style.

But how do you know if a change will make the car perform better or worse?

photo taken from the front of an electric race car before the start of the race as teacher carries out final checks with students, driver sitting and ready in car

As part of Connected Hull, we worked with Francis Askew Primary School to investigate collecting data on the forces that were exerted on a car as it raced.

They mounted a 3-axis accelerometer on their race car and used it to measure acceleration. The data was collected with a Raspberry Pi with a LoRaWAN interface, which enabled it to transmit the data, and a sensor board. It was powered by a USB battery pack.

Man holding raspberry pi with sensor hat and aerial to connect to the things network

The graph below shows the magnitude of acceleration and hence the forces acting on the car.

From this we were able to see some oscillations present, and at which points acceleration dropped. Analysing the results the team concluded that, in theory, the car was capable of reaching a higher top speed and reaching that speed faster.

graph showing acceleration data from a car built by 9-11 year olds for Project Blyth

It’s important to remember that these projects are about learning experiences for everyone; unfortunately the sensor was able to move so we couldn’t break down the data to determine the cause of the oscillating forces on race day. However, the collaboration demonstrated the potential of improving race performance as a result of collecting data to inform decision making.

connected hull team member sharing data to teacher on laptop screen

How does the the team intend to secure pole position in future years? They already have plans and ideas about using data and sensors as part of their future builds.

Hear some of their insights on the podcast below:


Images and podcast by Jerome Whittingham

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Headline image for Race Day Telemetry in Hull with Project Blyth

Race Day Telemetry in Hull with Project Blyth

Introduced to Vaughn Curnow from Project Blyth earlier this year, we were gripped within minutes by the exciting learning opportunities offered by the programme!

Run by the Greenpower Education Trust, Sunday 16th July 2017 saw the culmination of many collaborations centred around inspiring young people through STEM.

Teams of students, ranging in age from 9 years to Post-16, raced single seat electric cars that they'd built over time with the support of industry mentors. The circuit was located around the KCOM Stadium in Hull.

photo taken from the front of an electric race car before the start of the race as teacher carries out final checks with students, driver sitting and ready in car

Our Connected Hull project was able to support by offering research and trials of telemetry possibilities via The Things Network, particularly to teams we'd worked with during prototype phases of hardware and software.

One students pushing the team's Project Blyth race car on the tarmac before the race with driver ready, photo from side angle

One school was Francis Askew Primary in Hull, and you can hear their team of 9-11 year old engineers talking about using sensors and data collection to impact on their own driving performance.

The podcast below also includes snippets from their teacher about how future developments with sensor technology can support them with particular aspects of car efficiency.

We'll share data and a closer look at the technology added to the builds in the next blogpost.

teacher doing final checks on the car before Project Blyth race with adult ready holding a chequered flag to start

Images and podcast by Jerome Whittingham

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Headline image for Live coding with live (Hull) data

Live coding with live (Hull) data

Empowering others to 'make the world a better place through digital making' has been the project's fundamental aim from the beginning.

Projects in schools, team challenges to solve real world problems, individual project builds and community events are all contributing to an ever increasing open data set for others to share and use themselves via The Things Network Hull.

Sam Aaron using Sonic Pi to create music by live coding

Here's a taster of how we've started to share these activities through creative projects and build on developing digital skills.

This time the storytelling is based on a piece of music which has been live coded from a live data stream coming from a weather station project built at Hull Raspberry Jam.

Live and live?

Here's Sam Aaron linking the live temperature data feed into The Things Network Hull (logged via the Enviro pHat on a Raspberry Pi) into a live coding test using Sonic Pi v3.


A definite taster of things to come.

Watch (or rather, listen) out for more data stories through music over the coming weeks.

How will our data from Hull finally sound?

Images by Jerome Whittingham

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