Next training: 15-17th May 2024

Deadline to apply: 30 Apr 2024

Course overview

This short course will explore the fundamentals of build-it-yourself environmental sensors, including wiring and coding a simple logger, and other considerations.

We are running this course to empower more early career researchers to tap into the enormous opportunities to incorporate build-it-yourself environmental sensors into their research programmes.

The course will cover technical and theoretical material. We will instruct participants in the construction, wiring and coding of a simple particulate logger powered by Arduino software and hardware. Unique to this course compared with written guides and online schematics is participants’ opportunity to learn from our cumulative experience and discuss with us best practices to confront common pitfalls such as weatherproofing, power supply and data communication.  and all the other critical considerations to successfully deploy and obtain research-grade data from purpose-built sensors.

Our vision is that participants complete the course better placed to overcome common pitfalls and maximise their efforts in the acquisition of environmental data.

Aims

This three-day course will include laboratory practicals, discussion and roundtables and a field excursion. By the end of the course, participants will:

  • Have learned how to read a wiring schematic and code scripts to construct a simple environmental sensor;
  • Conducted data collection and performance assessment using central London as an outdoor laboratory;
  • Have an understanding of best practice when designing bespoke sensors and planning sensor deployments;
  • Be aware of likely pitfalls during each stage of sensor design, deployment and recovery and options to circumvent or minimise risks;
  • Observe and operate a large-scale, cloud-connected environmental sensor network (Freestation) during a field visit to the Thames Estuary.

Please note that the course is not an opportunity to receive troubleshooting diagnoses and technical support on existing bespoke sensor designs, nor do we have the capacity to respond to individual queries after the course.

About the teaching staff

The course leaders from the Department of Geography, King’s College London, have been at the forefront of developing bespoke, low-cost environmental sensors for several years (see Chan, Schillereff et al., 2020Pearce, Chadwick & Francis, 2022). We have designed and deployed equipment for monitoring aquatic, terrestrial and atmospheric settings across the UK and in many other countries (freestation.org; porelparamo.org). We are similarly embedding sensor design and deployment into our undergraduate and postgraduate taught curriculum. This short course is designed to share our collective expertise to support and accelerate the take-up of bespoke environmental sensors.

Short course programme

Day 1

Course introduction & electronics basics

An overview of current and previous research projects that employ build-it-yourself sensors; A hands-on practical to construct and code an particulate sensor followed by a data collection exercise in central London to test and evaluate sensor functionality.

Day 2

Fieldtrip demonstrating Deployment & considerations

A field excursion to the Thames Estuary to observe the Freestation network and discussion of best practice in deployment networked, cloud-connected environmental sensors.
Course social and dinner in the evening.

Day 3

Advanced design (technical details, enclosures & pitfalls)

A laboratory practical on more advanced technical concepts including prototyping, housing and weatherproofing, 3D printing. A roundtable discussion on common pitfalls and approaches to overcome.

Who can attend?

The course is open to any NERC-funded PhD student as a first priority, though other researchers are welcome to apply. We want everyone to feel welcome to apply and comfortable to attend the course. Environmental and geoscience and electrical engineering are not demographically diverse disciplines and we are committed to avoiding propagating inequalities.

Our expectations

No expertise in Arduino/Raspberry Pi, coding or electronics is necessary! We do expect attendees to have a sound sense for the following:

  • what a data logger is and how it operates;
  • The principles of data logging and using sensors for environmental and geoscientific research;
  • Some of the potential challenges when measuring environmental processes in the field.

Those with considerable expertise in these areas are welcome to apply but are reminded that this is not a trouble-shooting course.

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Next steps:

If interested in attending our next training session, please register your interest here or scan the QR code.

Questions? Please use our contact form.