Low-Cost Environmental Sensor Networks: Recent Advances and Future Directions

The use of low-cost sensor networks (LCSNs) is becoming increasingly popular in the environmental sciences and the unprecedented monitoring data generated enable research across a wide spectrum of disciplines and applications. However, in particular, non-technical challenges still hinder the broader development and application of LCSNs. This paper reviews the development of LCSNs over the last 15 years, highlighting trends and future opportunities for a diverse range of environmental applications. We found air quality, meteorological and water-related networks were particularly well represented with few studies focusing on sensor networks for ecological systems. Furthermore, we identified bias towards studies that have direct links to human health, safety and livelihoods. These studies were more likely to involve downstream data analytics, visualisations, and multi-stakeholder participation through citizen science initiatives. However, there was a paucity of studies that considered sustainability factors for the development and implementation of LCSNs. Existing LCSNs are largely focussed on detecting and mitigating events which have a direct impact on humans such as flooding, air pollution or geo-hazards, while these applications are important there is a need for future development of LCSNs for monitoring ecosystem structure and function. Our findings highlight three distinct opportunities for future research to unleash the full potential of LCSNs: (1) improvement of links between data collection and downstream activities; (2) the potential to broaden the scope of application systems and fields; and (3) to better integrate stakeholder engagement and sustainable operation to enable longer and greater societal impacts.

[1]  W. Lahoz,et al.  Mapping urban air quality in near real-time using observations from low-cost sensors and model information. , 2017, Environment international.

[2]  Carlo Ratti,et al.  End-user perspective of low-cost sensors for outdoor air pollution monitoring. , 2017, The Science of the total environment.

[3]  Xinyu Xing,et al.  Developing a data‐transfer model for a novel Wildlife‐tracking network , 2012 .

[4]  Alena Bartonova,et al.  Node-to-node field calibration of wireless distributed air pollution sensor network. , 2018, Environmental pollution.

[5]  Dora Marinova,et al.  Resilience thinking: a bibliometric analysis of socio-ecological research , 2013, Scientometrics.

[6]  Wilhelm Claupein,et al.  A Sensor Web-Enabled Infrastructure for Precision Farming , 2015, ISPRS Int. J. Geo Inf..

[7]  Stefan Pohl,et al.  Potential of a low‐cost sensor network to understand the spatial and temporal dynamics of a mountain snow cover , 2014 .

[8]  Kirk Martinez,et al.  Environmental Sensor Networks: A revolution in the earth system science? , 2006 .

[9]  Poonam J. Prasad Recent trend in wireless sensor network and its applications: a survey , 2015 .

[10]  F. Hobbs,et al.  Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis , 2016, PloS one.

[11]  T. Karpouzoglou,et al.  Advancing adaptive governance of social-ecological systems through theoretical multiplicity , 2016 .

[12]  Christos Makropoulos,et al.  An ontology framework for decentralized water management and analytics using wireless sensor networks , 2016 .

[13]  Seyyed Majid Mazinani,et al.  PRESENTING AN OPTIMAL ALGORITHM BASED ON FIREFLY ALGORITHM WITH SPECIFIC PARAMETERS TO SELECT THE CLUSTER HEAD IN WIRELESS SENSOR NETWORKS IN ORDER TO REDUCE ENERGY CONSUMPTION , 2017 .

[14]  Federico Viani,et al.  Wireless Sensor Network: A Pervasive Technology for Earth Observation , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[15]  Observing local CO2 sources using low-cost, near-surface urban monitors , 2018, Atmospheric Chemistry and Physics.

[16]  M. Rogulski Using Low-Cost PM Monitors to Detect Local Changes of Air Quality , 2018 .

[17]  Lucia L. Prieto-Godino,et al.  Open Labware: 3-D Printing Your Own Lab Equipment , 2015, PLoS biology.

[18]  Jeffery S. Horsburgh,et al.  A data management and publication workflow for a large-scale, heterogeneous sensor network , 2015, Environmental Monitoring and Assessment.

[19]  Brandon P. Wong,et al.  Open storm: a complete framework for sensing and control of urban watersheds , 2017, ArXiv.

[20]  Davide Brunelli,et al.  Wireless Sensor Networks , 2012, Lecture Notes in Computer Science.

[21]  J. D. Jabro,et al.  Wireless lysimeters for real-time online soil water monitoring , 2011, Irrigation Science.

[22]  Jó Ueyama,et al.  Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks , 2015, Comput. Geosci..

[23]  Ryan N. Smith,et al.  Development of a portable water quality sensor for river monitoring from small rafts , 2016, OCEANS 2016 MTS/IEEE Monterey.

[24]  V M van Zoest,et al.  Outlier Detection in Urban Air Quality Sensor Networks , 2018, Water, Air, & Soil Pollution.

[25]  Andrew J. Rettig,et al.  An open source software approach to geospatial sensor network standardization for urban runoff , 2014, Comput. Environ. Urban Syst..

[26]  Max Ritts,et al.  Smart Earth: A meta-review and implications for environmental governance , 2018, Global Environmental Change.

[27]  Steven R. Weller,et al.  A real-time ambient air quality monitoring wireless sensor network for schools in smart cities , 2015, 2015 IEEE First International Smart Cities Conference (ISC2).

[28]  Gb Stewart,et al.  The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks , 2013 .

[29]  Dick Botteldooren,et al.  Multi-criteria anomaly detection in urban noise sensor networks. , 2014, Environmental science. Processes & impacts.

[30]  Stefan Krause,et al.  Frontiers in real‐time ecohydrology – a paradigm shift in understanding complex environmental systems , 2015 .

[31]  K.J. Bengston,et al.  Design & Performance of a Networked Ad-hoc Acoustic Communications System using Inexpensive Commercial CDMA Modems , 2007, OCEANS 2007 - Europe.

[32]  Pedro Sánchez,et al.  Wireless Sensor Networks for precision horticulture in Southern Spain , 2009 .

[33]  Janet Elizabeth Hope Open Source , 2017, Encyclopedia of GIS.

[34]  Melisa Acosta-Coll,et al.  Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin , 2018, Natural Hazards.

[35]  Ivan B. Šećerov,et al.  Progressing urban climate research using a high-density monitoring network system , 2019, Environmental Monitoring and Assessment.

[36]  E. Snyder,et al.  The changing paradigm of air pollution monitoring. , 2013, Environmental science & technology.

[37]  Kai Walter Development of an early warning information infrastructure using spatial web services technology , 2010, Int. J. Digit. Earth.

[38]  Massimiliano Cannata,et al.  Boosting a Weather Monitoring System in Low Income Economies Using Open and Non-Conventional Systems: Data Quality Analysis , 2019, Sensors.

[39]  J. Suardiaz,et al.  GAIA2: A multifunctional wireless device for enhancing crop management , 2015 .

[40]  J. Byrne,et al.  The benefits of publishing systematic quantitative literature reviews for PhD candidates and other early-career researchers , 2014 .

[41]  Narendra Singh Raghuwanshi,et al.  Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges , 2015, Comput. Electron. Agric..

[42]  Nick van de Giesen,et al.  The Trans‐African Hydro‐Meteorological Observatory (TAHMO) , 2014 .

[43]  R. M. Lark,et al.  Characterising the within-field scale spatial variation of nitrogen in a grassland soil to inform the efficient design of in-situ nitrogen sensor networks for precision agriculture , 2016 .

[44]  Janae Csavina,et al.  PARduino: a simple and inexpensive device for logging photosynthetically active radiation. , 2014, Tree physiology.

[45]  G. La Loggia,et al.  The SESAMO early warning system for rainfall-triggered landslides , 2016 .

[46]  C. Mulrow The medical review article: state of the science. , 1987, Annals of internal medicine.

[47]  Contributions from M. Walpole The Millennium Development Goals Report , 2008 .

[48]  Daniel Coca,et al.  Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities—a case study in Sheffield , 2019, Environmental Monitoring and Assessment.

[49]  Petr Kubíček,et al.  Prototyping the visualization of geographic and sensor data for agriculture , 2013 .

[50]  Feng Mao,et al.  Water sensor network applications: Time to move beyond the technical? , 2018, Hydrological Processes.

[51]  Alena Bartonova,et al.  Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates? , 2017, Environment international.

[52]  Olivier Berder,et al.  Architecture exploration of multi-source energy harvester for IoT nodes , 2016, 2016 IEEE Online Conference on Green Communications (OnlineGreenComm).

[53]  Alessandro Fassò,et al.  A statistical approach to crowdsourced smartphone-based earthquake early warning systems , 2015, Stochastic Environmental Research and Risk Assessment.

[54]  Wei Liu,et al.  Citizen science for hydrological risk reduction and resilience building , 2018 .

[55]  A. Shusterman,et al.  Observing local CO2 sources using low-cost, near-surface urban monitors , 2018, Atmospheric Chemistry and Physics.

[56]  David G. Rossiter,et al.  Past, present & future of information technology in pedometrics , 2018, Geoderma.

[57]  Gerhard P. Hancke,et al.  Open Hardware: A Role to Play in Wireless Sensor Networks? , 2015, Sensors.

[58]  Teresa Vazão,et al.  A wireless sensor network for monitoring volcano-seismic signals , 2014 .

[59]  N. Raghuwanshi,et al.  Wireless sensor networks for agriculture : The state-ofthe-art in practice and future challenges , 2015 .

[60]  M. Srbinovska,et al.  Environmental parameters monitoring in precision agriculture using wireless sensor networks , 2015 .

[61]  David Hannah,et al.  Real-time monitoring of nutrients and dissolved organic matter in rivers: Capturing event dynamics, technological opportunities and future directions. , 2016, The Science of the total environment.

[62]  Carlos Bartesaghi Koc,et al.  Evaluating the cooling effects of green infrastructure: a systematic review of methods, indicators and data sources , 2018 .