Difference between revisions of "Sensor Data Acquisition"

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====Reliability and Redundancy====
====Reliability and Redundancy====
of transmission mode and of equipment
of transmission mode and of equipment
Plug-n-play vs.
Plug-n-play vs.

Revision as of 10:20, April 22, 2014

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Traditionally, environmental sensor data from remote field sites were manually retrieved during infrequent site visits. However, with today's technology, these data can now be acquired in real-time. Indeed, there are several methods of automating data acquisition from remote sites, but there is insufficient knowledge among the environmental sensor community about their availability and functionality. Moreover, there are several factors that should be taken into consideration when choosing a remote data acquisition method, including desired data collection frequency, bandwidth requirements, hardware and network protocols, line-of-sight, power consumption, security, reliability and redundancy, expertise, and budget. Here, we provide an overview of these methods and recommend best practices for their implementation.


The classic method of acquiring environmental sensor data from remote field sites involves routine technician site visits, in which s/he connects a laptop to a datalogger, an electronic device that records sensor data over time, and manually downloads data recorded since the last site visit. Once the technician returns to the lab, s/he is then responsible for manually uploading these data to a server for later processing and archival.

While manual acquisition methods are generally effective, there are many reasons to automate environmental sensor data acquisition. For instance, if the site is not visited frequently enough, the datalogger memory can become full and depending on how the datalogger is programmed, sensor data will either overwrite itself or stop recording entirely. This situation often occurs at remote sites that become periodically inaccessible due to environmental conditions, such as heavy winter snow pack. Second, the burden of responsibility for not only the successful retrieval of the sensor data, but also the subsequent upload to a server for safekeeping, lies solely on the technician. Moreover, with any instrumented site, there is the inherent potential for sensor or power failure. Automated data acquisition systems allow technicians to learn of such issues prior to visiting the field site, reducing the potential for data loss. Finally, automated data acquisition methods save hundreds of person hours and vehicle miles that would have otherwise been spent manually acquiring data or troubleshooting unanticipated problems, thus improving the overall quality of the data.

Bidirectional communication methods have the additional advantages of allowing technicians to remotely change system settings, test configurations, and troubleshoot problems. These methods also open the field to a wide variety of devices that may be deployed at a remote field site, such as controllable cameras, on-site wireless hotspots, and IP-enabled control or automation equipment.


The decision of which sensor data acquisition method to use at a given site requires the careful consideration of many factors, for which we provide an overview here.

Collection Frequency

What is the desired collection frequency? How important is real-time accessibility? For instance, the data could be retrieved in near real-time (every few minutes to every few hours) or just once or twice per day. High frequency datasets or images should be collected more frequently.


Bandwidth can be an important consideration, particularly when high frequency data are being collected. Will cameras be utilized at the site? Where is broadband point of presence (POP) located? Does equipment work with required bandwidth? More frequent collection intervals require less bandwidth per transmission are are recommended for high frequency datasets or for images.



Many dataloggers only have serial (RS232) ports, therefore requiring a serial-to-ethernet converter to interface with automated acquisition instrumentation. USB.


Private vs public IP networks.


Evaluation of environment, topography, and vegetation. Can be initially determined using LOS calculators, which use DEM models, but must be ground truthed. Often requires a repeater infrastructure. Choosing repeater locations involves many of the same considerations for choosing site selection. Distance to repeater is a factor. Automated sensor data acquisition methods require many of the same site selection considerations discussed in Sensor Site and Platform Selection, particularly when selecting repeater sites.


How important is real-time accessibility? (e.g., what is desired collection frequency?). What are the transmission type power requirements, onsite buffer size. Redundancy is preferred, especially in very remote sites. If power is disrupted, will system resume operations?


Physical Security

see Sensor, Site, and Platform Selection

Network Security

Encryption keys, VPN

Reliability and Redundancy

of transmission mode and of equipment


Plug-n-play vs.


Costs of implementing a data acquisition and transmission method depend on existing infrastructure, initial setup costs including personnel, personnel costs, specifically technician maintenance, and recurring costs, such as monthly recurring costs with cellular transmission.


There are three main categories of remote data acquisition methods: manual, unidirectional telemetry, and bidirectional telemetry. Each has advantages and disadvantages in terms of infrastructure, cost, reliability, required expertise, and power consumption.


This method involves scheduled visits to the site by a field technician, who uses a serial-to-computer connection and/or flash memory transfer of environmental sensor data to their laptop or similar device. Upon returning from the field, the technician is responsible for manually uploading these data to a server. This acquisition method is simple and may be the only option when site instrumentation generates large data files. However, this method provides no real-time data access and therefore, no knowledge of instrumentation failures. Moreover, the reliability of this method is completely dependent on the technician.



Best Practices

collection interval for high frequency data and images.

Case Studies