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 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 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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Headline image for Engaging Student Voice through Project-Based Environmental Learning

Engaging Student Voice through Project-Based Environmental Learning

Access to STEM activities, and problem-based approaches to learning, are at the heart of this Connected Hull programme.

That’s seen us tailoring schools’ challenges to explore areas of global citizenship, and project-based learning methodology to solve real-world challenges facing local communities.

Codebug with sensor board

Sensor technologies currently available for Citizen Science approaches support students to collaborate on a range of environmental issues and make a positive impact on their own community.

One of the first projects has been to measure UV levels. That's using the power of student voice to support peers, raise awareness and educate others about harmful levels and how to protect against them.

If you're interested in the code used to facilitate projects created by children from age 7+ years, then you'll find it here.

Showing code to download onto a sensor node and measure uv levels

We’re facilitating workshops where young digital makers are using their computing skills to design, build and take innovative student-driven research projects into their chosen environments.

And then share their finding and creative solutions to a wider audience.

Codebug wearable tech being used to measure UV and show as lights on the LED ring

An introductory workshop using Codebug as a wearables project has allowed us to introduce the opportunities available through Citizen Science and IOT.

Initial data collection includes temperature , air pressure, humidity, altitude and GPS. The new air quality board will also be used to support the next programme of workshops over the Summer.

Children and communities will, however, be able to use their code with sensor nodes and link their environmental data and findings from this first phase of projects to the Connected Hull dashboard and coverage through The Things Network for Hull.

Through this approach we’re discussing the benefits, applications and considerations of big data, GPS metadata and privacy of personal data before adding to future project builds.

Codebug wearable tech used to measure UV and visuallise on string of leds

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Headline image for Winners at The Big Chip Awards for IOT impact!

Winners at The Big Chip Awards for IOT impact!

We're thrilled to be part of the 'Things North' collaboration and to be sharing plans, ideas and aspirations with others, which include projects launched in Manchester, Calderdale, Leeds, Bradford and Liverpool.

Map showing things network gateways located across the north of england

Last week's award recognised the impact of our activities across the region, with one judge's comment as:

"Things North deserve recognition for making the first positive inroads into facilitating the IoT project by joining the globally growing LoRaWAN network and by fostering the regional growth of the network."

Further details here.

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