Reducing the Carbon Footprint for Remote Sampling of Environmental Samples

Reducing the Carbon Footprint for Remote Sampling of Environmental Samples

Supervisors:Dr Terry Payne(University of LiverpoolComputer Science)

Sam Goddard (Labmotive)

Reference:UoL-LCEI-138

Application Deadline: 30thAugust 2016

Introduction:

The University of Liverpool (UoL) and Labmotive are seeking to appoint a suitably experienced and qualified individual to undertake a three year doctoral research programme. The PhD will be focused developing an algorithm for remote sampler software.

A large number of analytical laboratories perform quality control on environmental samples for water control, soil analysis or ecological surveys. This control is mandatory to check if quality regulations are met (i.e. for water samples) and to monitor environmental pollution. Individual organisations may collect more than 100 000 samples annually, which quickly scales up to several million samples per year for the UK alone. Yet, the majority of these samples are collected remotely, as samples are often distributed over large areas. Usually, the sampling process involves a fleet of employees traveling to sample locations, producing a large carbon footprint of several hundred thousand tons of CO2 emission every year.

Labmotive Ltd seeks to minimise the carbon footprint of remote sampling by developing a new organisation system for sample collection. This system should implement the carbon emission as an inherent optimisation parameter and adjust work routines such as sampling routes and times. As a centrepiece of this system, Labmotive provides a technology called Remote Sampler, which allows a centralised management team to give instructions to, and extract data from, handheld devices operated by employees out in the field. The challenge of the proposed project would be the design of software algorithm for a new sampling schedule within the Remote Sampler software, which includes a dynamic optimisation model for pollution parameters to reduce carbon emission.

Overall aim:

The aim of the project is to develop an algorithm for the Remote Sampler software that adjusts the key parameters of remote sampling to efficiently reduce the overall carbon footprint. Labmotive aims for a reduction of least 20% of the overall CO2 emission for each company applying Remote Sampler.3 This aim shall be achieved by ample objectives:

The developed software algorithm shall calculate the carbon footprint of remote sampling as precisely as possible by taking all related parameters into account. These parameters could be suboptimal-routes between sampling points or unforeseen additions of new sampling locations. The software solution shall also include generalised rules imposing constraints on the sampling process, depending on the type of business. Although Labmotive proposes a first prototype specifically designed for water samples, the general principle needs to be adjustable to all sorts of samples and related organisations.

An important feature of the new software solution must be a dynamic update and re-modelling of the sampling schedule as soon as changes to the work routine appear. This dynamic mechanism shall provide a real time optimisation of sampling schedules for each field employee and might link to further machine learning elements, improving the carbon footprint over time. In order to guarantee an optimum support for this kind of software design, UoL’s Computer Science Department joined this project and will provide help on machine-learning algorithms.

For an immediate response and modification of sampling schedules, the software application needs to communicate with field employees constantly. As a core part of this project, Labmotive provides Remote Sampler, a product of advanced technology that enables an instant broadcast of all relevant information to employees collecting samples. Remote Sampler is a mobile device based data capture system which allows a centralised management system to assign work to GPS enabled, handheld devices used by field employees. In addition, all sample information provided by the field employee can be extracted from the devices and is fed into a database by the Remote Sampler software, which schedules work flows. The constant communication between the handheld devices and the software would allow the planned algorithm to dynamically adjust and optimise the sampling schedule for low carbon footprint. Remote Sampler is currently used across the UK in Water and Environmental sectors and therefore builds an ideal base for the planned software solution to be installed nationwide.

Low Carbon Eco-Innovatory

This PhD is one of 20 industry-led collaborative R&D projects from the Low Carbon Eco-Innovatory. The aim of the project is for you to work toward a PhD at the University of Liverpool through delivering ‘real – life’ solutions to industry. The Centre brings together the expertise, resources and global contacts of University of Liverpool, Liverpool John Moore’s University and Lancaster Universityto create innovative low carbon goods, processes and services developed through collaborative R&D partnerships between local companies in the Liverpool City Region and local universities.

All LCEI PhD projects have been developed by SMEs contacting the University for assistance in R&D where the company does not have internal expertise, resource or facilities to carry out the research. This will give you a strong advantage in entering a competitive jobs market in both the academic and commercial sectors.

By joining the centre you will receive a £15,000 tax free stipend per year, with your post-graduate tuition fees paid (at UK/EU rate). The Centre is part financed by the European Regional Development Fund. Please visit for more information on the centre.

Application details:

To apply for this opportunity please email oting UoL-LCEI-138 in the email subject with:

• 2 page CV
• 2 page expression of interest
• A completed Application Criteria – available from

Further information:

Labmotive (formerly Labmobility) was founded in 2006 to provide unique software for mobile systems in and around analytical laboratories. Our aim is to provide the world’s leading software for both mobile laboratory instrument/LIMS interconnectivity and remote sampling.Please visit for more information

Department of Computer Science, University of Liverpool. The 2014 Research Excellence Framework rated 97% of our research as being world-leading or internationally excellent, the highest proportion of any CS department in the UK.

With our close industry partnerships and Russell Group status we enjoy strong funding and have recently invested £5m in our facilities. It is the perfect setting for world class experts to do ground-breaking research.

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The current research platforms are grouped into two main sections, each containing a number of more specialised areas. Please visit for more information.