Imperial College London

Nick S Jones

Faculty of Natural SciencesDepartment of Mathematics

Professor of Mathematical Sciences



+44 (0)20 7594 1146nick.jones




301aSir Ernst Chain BuildingSouth Kensington Campus






BibTex format

author = {Sethi, S and Ewers, R and Jones, N and Orme, D and Picinali, L and Sethi, SS and Ewers, R and Jones, N and Orme, CDL and Picinali, L},
doi = {10.1111/2041-210X.13089},
journal = {Methods in Ecology and Evolution},
pages = {2383--2387},
title = {Robust, real-time and autonomous monitoring of ecosystems with an open, low-cost, networked device},
url = {},
volume = {9},
year = {2018}

RIS format (EndNote, RefMan)

AB - 1. Automated methods of monitoring ecosystems provide a cost-effective way to track changes in natural system's dynamics across temporal and spatial scales. However, methods of recording and storing data captured from the field still require significant manual effort. 2. Here we introduce an open source, inexpensive, fully autonomous ecosystem monitoring unit for capturing and remotely transmitting continuous data streams from field sites over long time-periods. We provide a modular software framework for deploying various sensors, together with implementations to demonstrate proof of concept for continuous audio monitoring and time-lapse photography. 3. We show how our system can outperform comparable technologies for fractions of the cost, provided a local mobile network link is available. The system is robust to unreliable network signals and has been shown to function in extreme environmental conditions, such as in the tropical rainforests of Sabah, Borneo. 4. We provide full details on how to assemble the hardware, and the open-source software. Paired with appropriate automated analysis techniques, this system could provide spatially dense, near real-time, continuous insights into ecosystem and biodiversity dynamics at a low cost.
AU - Sethi,S
AU - Ewers,R
AU - Jones,N
AU - Orme,D
AU - Picinali,L
AU - Sethi,SS
AU - Ewers,R
AU - Jones,N
AU - Orme,CDL
AU - Picinali,L
DO - 10.1111/2041-210X.13089
EP - 2387
PY - 2018///
SN - 2041-210X
SP - 2383
TI - Robust, real-time and autonomous monitoring of ecosystems with an open, low-cost, networked device
T2 - Methods in Ecology and Evolution
UR -
UR -
VL - 9
ER -