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Efficient power consumption strategies for stationary sensors connected to GSM network

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The number of large sensor systems are rapidly growing nowadays in many fields. Well-designed Big Data solutions are able to manage the enormous data flow and create real business benefits. One dynamically growing application area is precision farming. It requires robust and energy-efficient sensors, because the devices are placed outdoors, often in harsh conditions, and there is no power outlet in the middle of a corn field. Power efficiency is one of the major themes of the Internet of Things (IoT). According to the IoT vision , embedded sensors send their data to processing units (either located near to the sensor or on some intermediate gateway device or in the cloud) using heterogeneous transport networks. Some sensors employ short-range network like Bluetooth and some gateway device like a tablet. Other sensors directly connect to wide-area networks like cellular networks. This paper will analyse different communication patterns accomplished over GSM network from the viewpoint of the energy consumption of the sensor device with the assumption that the sensor is stationary. The measurements were done using two different GSM modems designed for embedded systems to ensure that the results represent a wider picture and not some implementation property of a particular GSM modem. Recommendations are given about the strategies applications should follow in order to minimize the energy consumption of their GSM subsystems.
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Efficient power consumption strategies for stationary sensors connected
to GSM network
G´
abor Paller, P´
eter Sz´
armes and G´
abor ´
El˝
o
Sz´
echenyi Istv´
an University, Information Society Research & Education Group, Egyetem t´
er 1. Gy ˝
or, Hungary
{paller.gabor,peter.szarmes,elo}@sze.hu
Keywords: agriculture, sensors, power efficiency
Abstract: The number of large sensor systems are rapidly growing nowadays in many fields. Well-designed Big Data
solutions are able to manage the enormous data flow and create real business benefits. One dynamically
growing application area is precision farming. It requires robust and energy-efficient sensors, because the
devices are placed outdoors, often in harsh conditions, and there is no power outlet in the middle of a corn field.
Power efficiency is one of the major themes of the Internet of Things (IoT). According to the IoT vi-
sion, embedded sensors send their data to processing units (either located near to the sensor or on some
intermediate gateway device or in the cloud) using heterogeneous transport networks. Some sensors employ
short-range network like Bluetooth and some gateway device like a tablet. Other sensors directly connect to
wide-area networks like cellular networks.
This paper will analyse different communication patterns accomplished over GSM network from the
viewpoint of the energy consumption of the sensor device with the assumption that the sensor is stationary.
The measurements were done using two different GSM modems designed for embedded systems to ensure
that the results represent a wider picture and not some implementation property of a particular GSM modem.
Recommendations are given about the strategies applications should follow in order to minimize the energy
consumption of their GSM subsystems.
1 Introduction
Internet of Things is often considered a recent
trend but the vision was presented first in 1991
(Weiser, 1991). Weiser envisioned computers that
”disappear into the background” and are connected
with wired or wireless links. One key element of
Weiser’s ubiquitous computing was the low-power
nature of the computing elements that are able to
function for an extended period of time without
recharging otherwise battery issues would prevent
the devices from ”disappearing into the background”.
Low-power and ultra low-power energy consumption
has been a key IoT research theme ever since (Sund-
maeker et al., 2010), (Zorzi et al., 2010).
IoT systems employ heterogeneous networks to
connect the sensors to the data processing units. Some
solutions are based on short-range networks (e.g. Zig-
Bee, Bluetooth), the data is collected by some ”gate-
way” device (e.g. smartphone, tablet, set-top box)
which then connects to a wide-area network. Isolated
sensors that are rarely visited by humans and are far
from any other elements of the ubiquitous network
cannot adopt this solution, these sensors have to con-
nect to the wide-area network directly. The most com-
mon wide-area network with low connectivity cost
and large coverage is the public cellular network.
2 The AgroDat project
Today sensors and sensor networks gain more and
more importance in many application areas. Ma-
chines (including cameras, sensors, satellites, imag-
ing devices, etc.) are already generating more data
than we, humans and business processes (Figure 1).
These devices often operate in a harsh environment
without access to electric networks, where robustness
and energy efficiency are very important characteris-
tics.
One such application field is agriculture. Preci-
sion agriculture is an integrated agricultural manage-
ment system incorporating several technologies. This
technology can reduce the cost of producing crops
and the risk of environmental pollution (Earl et al.,
1997). The AgroDat R&D project with notable in-
dustrial and scientific partners aims to build an agri-
cultural information system in Hungary. The system
relies on collecting and analyzing high-volume data
about crops and environmental conditions, like soil
moisture and temperature, air temperature, precipita-
tion, solar radiation, etc.
Soil sensors (see Figure 2) can measure water po-
tential, electric conductivity, volumetric water con-
tent, soil temperature etc. Electric conductivity corre-
lates with salt content, influencing plant growth. Wa-
ter potential refers to the water available for plants.
This data can be used for planning irrigation, fore-
casting plant diseases, and analyzing soil aspiration.
Light sensors (see Figure 2) can measure the inten-
sity of photosynthetically active radiation, or the spec-
trum of incoming and reflected light in certain bands,
which can then be used to calculate the Normalized
Difference Vegetation Index and Photochemical Re-
flectance Index (Garrity et al., 2010). These indexes
correlate closely with vegetation and photosynthetic
activity respectively, and they are good indicators
of biomass and plant stress. Sensors can measure
relative humidity, air temperature or vapor pressure.
These values are linked with plant evaporation. Leaf
wetness sensors are designed to detect wetness (pres-
ence and duration) and ice formation on leaf surfaces.
The data is useful for forecasting plant diseases and
determining spraying actions.
Combining different sensors into a sensor group
creates synergies, and during the design of such a
sensor unit, low energy consumption and ability to
withstand harsh environmental conditions are impor-
tant objectives. Much of the data needed for the agri-
cultural information system can be collected by these
sensor units, which can make measurements even on
a minute-rate. Sensors are very different in terms of
their data communication requirements. The current
batch of agricultural sensors being developed by our
project have the following properties.
These sensors are stationary. Once installed, they
move very rarely.
Their environment changes only slowly. For ex-
ample sudden changes in ground temperature or
ground moisture are rare. This means that sensor
values can be sampled with quite long sampling
periods (multiple hours or even daily).
The quantity of the data to be transmitted is rel-
atively small. One measured quantity is a nu-
merical value and the sensor equipment measures
about 10-20 such quantities.
Figure 1: Sources of the data growth
Figure 2: Decagon soil and light sensors (source: Decagon)
These sensors are installed on locations that are
rarely accessed and are far from the usual net-
work infrastructure endpoints. For example one
of our sensors are meant to be installed on large
corn fields. Long, unassisted operation is an im-
portant requirement.
These requirements have led to the following
high-level design decisions.
The sensors will be connected using ordinary
GSM network directly, without the help of some
”gateway” node. Each sensor will be a GSM end-
point.
Low-bandwidth data bearers like SMS or GPRS
satisfy the transfer requirements.
Low energy consumption/long operating time
without on-site service is crucial.
Remote manageability of the sensor is a must.
The conceptual architecture of the system can be
seen in Figure 3.
3 Evaluated GSM modems
In order to ensure that we are really evaluating the
communication alternatives, we chose to run our mea-
surements from two different GSM modem vendors.
GL865-QUAD is a variant of Telit’s extremely
popular GE865 product family 1. The module has
1GL865-QUAD, http://www.telit.com/products/product-
service-selector/product-service-
selector/show/product/gl865-quad/
Figure 3: Conceptual architecture
2.5G network support which means that it can ac-
cess GSM (voice call and SMS) and GPRS network
services. The modules can be used in GSM modem
mode when the application code is executed by some
external CPU (e.g. a microcontroller) but a stan-
dalone mode is also available when the application
code is executed by the on-chip Python interpreter.
SIMCOM’s SIM900 module 2was selected to cross-
check the power consumption measurement results of
certain communication scenarios on a different GSM
modem implementation. It is a more traditional unit
in the sense that SIM900 needs an external CPU to
execute the application logic.
Power consumption measurements were accom-
plished with about 3 Hz sampling the filter capacitors
on the power lines filter out higher frequencies. The
samples were further analysed using the R/R Studio
mathematical suite 3.
4 Communication scenarios
4.1 Network registration
This is seemingly the simplest scenario but it comes
with the most complications. Registering on the net-
work and staying registered involves network regis-
tration and location update procedures but more im-
portantly, it requires that the GSM module is active
and listens to network events. As we assume station-
ary operation, procedures relevant to mobility man-
agement e.g. cell handover do not occur but in order
to stay registered on the network, periodic location
update has to be executed. Figure 4 shows the power
2SIM900 Specification,
http://wm.sim.com/downloaden.aspx?id=2972
3http://www.rstudio.com/
Figure 4: Telit GL865 power consumption (initial registra-
tion and location update)
consumption of the Telit GL865 executing this sce-
nario. The two spikes of power consumption are re-
lated to the network registration and location update
procedures. Location update occurs on the network
used during the measurements (Telenor Hungary) in
about every 55 minutes. This is a configuration value
chosen by the network operator and can be expected
to be between 30 minutes and 2 hours. Typically this
value is constant for the same network. It is more
important to note, however, that the idle power con-
sumption of the module is about 7mA. This means
that while the actual network procedures consume
720 mAs ( milliamper-second) for the network reg-
istration and 400 mAs for one location update (with
this network, there are about 26 location updates per
day which means about 10400 mAs or 2.89 mAh cost
for location updates), keeping the module operational
costs about 170 mAh for a day. Note that these val-
ues are relatively unaffected by the received signal
strength. The measurements were done with RSSI=5,
RSSI=4 and RSSI=2 signal strengths and the results
were very similar. The reason of this similarity is that
actual network transmission is very short in these sce-
narios.
The results are very similar with the SIM900 mod-
ule. Short power consumption spikes related to the
network registration and location update procedures
can be observed but it is more important to note the
idle current consumption of the module which is close
to 20 mA. While the network registration procedure
costs only 834 mAs and 26 location updates cost 2.71
mAh, keeping the module operational costs 456 mAh
for a day.
Both modules offer custom power saving modes.
The idea behind these modes is that only the func-
tional units executing GSM procedures remain opera-
tional, units communicating with the application CPU
(and in case of the Telit module, units executing the
application logic) are switched off. With these power
saving modes, the idle consumption of the devices de-
creases quite dramatically. For both the GL865 and
the SIM900, the idle power consumption falls below 1
mA. Specifically, for the GL865 the power consump-
tion needed to keep the module operational for a day
is about 11 mAh while network procedures cost ad-
ditional 2.9 mAh, resulting a total of 14 mAh for a
day. For the SIM900, the idle power consumption for
a day is about 23.3 mAh and network procedures add
2.71 mAh, resulting a total of about 26 mAh for a day.
These measurements show the importance of
implementation-specific power-save modes and high-
light the fact that the Telit GL865 is about twice more
efficient than the SIM900 when it comes to low-power
operation. It is a much more important observation,
however, that even with power-save modes active, the
continuous operation of the module has by far the
highest cost. For the Telit GL865, only 20% of the
power budget is spent on actual network procedures,
the remaining 80% is the cost of keeping the module
operational. The difference is more dramatic for the
less power-efficient SIM900: only 10% of the daily
power budget is spent on network operations, the re-
maining 90% is needed to simply keep the module
active.
4.2 Data communication
So far only the cost of being registered on the net-
work was calculated. Data communication comes
with additional costs. Our sensors send relatively
small amount of data (10-20 numerical values) rel-
atively rarely (1-2 times a day) so network bearers
with lower bandwidth were analysed. A wide vari-
ety of data encodings have been proposed for IoT ap-
plications but the area is far from settled. XML-based
formats (Su et al., 2014) and publish-subscribe frame-
works are being proposed for IoT (Hakiri et al., 2013).
Our intention was to keep the amount of data
transmitted, the power needed for data transmission
and the CPU cycles needed to encode/decode pack-
ets low so we adopted a size-efficient data encoding
based on ASN.1 and Basic Encoding Rules (BER)
(Kaliski and Jr., 1993). These BER data structures
were then sent to the server using HTTP implemented
on top of the modules’ native TCP support.
The power consumption was measured with in-
creasing amount of data items (16 bit values) using
the BER encoding mentioned earlier. With regards to
PDP context handling, two different approaches were
implemented. The first approach activates the PDP
context, sends the packet then deactivates the context.
This is closer to our data communication scenarios
when we send data packets only rarely. In order to
Data items Packet size
(bytes)
Power con-
sumption
(mAs)
16 287 2370
32 511 2595
64 1981 2945
128 4157 3307
256 8509 3951
Table 1: Power consumption of data communication, PDP
context activated/deactivated for each packet
Data items Packet size
(bytes)
Power con-
sumption
(mAs)
16 287 1987
32 511 2180
64 1981 2590
128 4157 3270
256 8509 3570
Table 2: Power consumption of data communication, PDP
context activated only once
evaluate the cost of PDP context activation, the sec-
ond approach activates the PDP context once, sends
all the test packets then deactivates the context after
all the packets are sent. Table 1 shows the results for
the first approach while Table 2 shows the results for
the second approach using the GL865 module. It can
be observed that PDP context activation adds a con-
stant but not too significant power cost to the commu-
nication scenario.
Conclusion is that data size/data format optimiza-
tion does matter when trying to lower power con-
sumption. To significantly increase power consump-
tion, however, data sizes must be several times larger
than the baseline data size. Optimization of data sizes
may be more relevant for ensuring data transfer in
case the radio path between the base station and the
sensor is not very optimal.
4.3 SMS bearer
Data may also be sent using short messsages, pop-
ularly called SMS. Binary SMS is often filtered by
operators so we employed Base64 encoding and sent
the ASN.1 BER content in textual format. Figure 5
shows the power consumption using the SMS bearer
with a 112 byte long data packet (which is actually
154 character long after Base64 encoding) and Fig-
ure 6 shows the sending of the same packet using
GPRS. Intuitively, it seems that SMS requires much
less power and it is indeed the case: GPRS requires
2347 mAs power while SMS needs only 247 mAs
Figure 5: Power consumption of the data transfer with SMS
Figure 6: Power consumption of the data transfer with
GPRS
power. The large difference is caused by the fact that
SMS uses signalling radio channels that are already
allocated when the module registered with the net-
work while GPRS has to allocate (and deallocate) ad-
ditional radio channel for the data transfer. SMS is
therefore attractive due to its much lower power con-
sumption requirement but quite frequently the pricing
of the subscription prevents using SMS extensively
for data transfer.
4.4 Push bearer
One strong requirement for our remotely placed sen-
sors is manageability because physically accessing
the sensors’ location is not always feasible. Manage-
ment operations are usually initated by the manage-
ment server operator asynchronously, independently
of the sensor’s scheduled operations. This requires a
push bearer that can be used to instruct the sensor to
contact the management server.
If the sensor is not registered to the network, such
an operation is impossible. The management server
operator may have to wait for the sensor to contact the
server when the sensor sends in its scheduled batch of
data and may send its management commands in the
context of the sensor data sending session. In case
of doubt (e.g. when an accident damaging the sensor
is suspected), the sensor’s health cannot be verified
immediately which may prevent timely maintenance
operations. Management requirements create a strong
incentive to register the sensor to the mobile network
continuously.
If the GSM module is registered continuously,
short message service (SMS) may be used to send
alert to the sensor to connect to the management
server for management operations. As we have seen,
SMS is very power-efficient and management opera-
tions are infrequent enough so that SMS pricing is not
so much of an issue. Another option is to simulate the
push bearer using TCP.
TCP-based push bearer simulation relies on the
sensor to maintain a TCP connection to the manage-
ment server. When the server wants to send a man-
agement packet, it may use the duplex nature of TCP
streams to send the packet to the sensor. Timeout
issues, however, make this solution tricky to imple-
ment. TCP timeouts on the sensor and on the server-
side can be controlled by the implementation but mo-
bile and backbone networks between the mobile net-
work gateways to the servers often employ Network
Address Translators (NATs) that remove IP address
associations for TCP streams that look idle. The
problem was demonstrated with a test program im-
plemented on both the GL865 and SIM900 modules
and a test server application deployed on a cloud-
based Windows Server. The GSM modules attached
to the mobile network (Telenor Hungary), opened a
TCP connection to the server and left the connection
idle. After a timeout expired, a packet was sent from
the server to the GSM module. It was found that the
maximum safe timeout period was 2 hours which is
consistent with the recommendations in (Guha et al.,
2008). Longer timeout resulted in the server and the
GSM module to be silently disconnected by some
NAT on the network without either of the commu-
nicating parties being aware of the disconnection.
The results were consistent with both GSM modules,
demonstrating that this behaviour is the property of
the network between the GSM module and the cloud-
based server. Without deeper investigation of the full
network topology, it is hard to say where the NAT was
located that terminated the connection.
Reliable implementation of the TCP-based push
bearer must use a heuristic algorithm (Price and Tino,
2010), (Haverinen et al., 2007) to estimate the time-
out between the GSM module and the server by send-
ing test packets with different timeouts. The heuris-
tic algorithm must also be prepared for the fact that
this timeout may also change dynamically, due to
changes in the network topology. Once that timeout is
known, a keepalive packet must be sent in any direc-
tion over the TCP stream to prevent any NAT that may
be present between the GSM module and the server
to terminate the connection. This keepalive operation
has a power consumption cost.
Both modules are able to wake up from power-
save mode when an incoming data packet arrives on a
TCP connection that has been opened previously. For
the GL865, the reception of one such packet costs 942
mAs. Using 2 hour timeout (hence 12 such packets
per day), the daily power consumption cost is about
3.1 mAh. The SIM900 performs better in this test,
the cost of one keepalive packet was 570 mAs which
means 1.9 mAh for a day. This means that the power
consumption cost of maintaining one TCP connection
is comparable to the cost of the location update oper-
ations that keep the module registered on the mobile
network. For the Telit GL865, such keepalive proce-
dure increases the daily power consumption by 22%.
For the SIM900, the increase is only 7% due to the
higher baseline power consumption of the module and
the better TCP packet reception power cost. It must
be noted that the GL865 also executed the application
logic for this test but the SIM900 acted only as a mo-
dem. TCP-based push bearer comes with other prob-
lems on the server-side like keeping a large amount
of TCP connections open at the same time but these
issues are not discussed in this paper.
5 Conclusions
Directly connecting a remotely located, battery-
powered sensor to the GSM network comes with a set
of compromises. In our case, the power consumption
and manageability requirements were in direct con-
flict with each other. From the power consumption
point of view, the best solution would be to attach
the sensor to the mobile network only for the dura-
tion of sending the scheduled measurement data pack-
age. This would also decrease the load on the mobile
network infrastructure in case of a large number of
sensors. This approach would make the sensors more
complicated to manage, however. In order to send a
management operation, the management server oper-
ator should wait until the sensor connects back to the
server for the scheduled data sending operation.
The compromise may be the power-saving mode
of the GSM modules. Both GSM modules we eval-
uated have such mode even though these features are
non-standard and are specific to the particular GSM
module. A daily consumption of 15-30 mAh means
80-160 days of operation with a low-cost 2400 mAh
battery pack. As special, high capacity batteries are
now commercially available, this operational time
may be increased dramatically.
Push bearer is required for asynchronous manage-
ment operations. SMS offers an attractive alternative.
TCP-based push bearer is possible to implement with
relatively minor increase of the power consumption
but is problematic to make reliable due to NAT issues
and limitations of the number of the TCP streams on
the server side.
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... Among the latter, 2D imaging sensors ( " cameras " ) have been found to be efficient in detecting effects of drought (Grant et al., 2006), (Alderfasi and Nielsen, 2001), plant phenotype (Li et al., 2014) or diseases (Moshou et al., 2004). AgroDat.hu is an ongoing research project funded by the Government of Hungary (Paller et al., 2015). In the first phase the project concentrated on sensors providing scalar value like soil temperature, soil moisture, concentration of salts in groundwater and CO 2 concentration in the ground, air temperature, humidity , rainfall, wind speed and direction, solar radiation intensity and leaf wetness. ...
... From the communication pattern and sensor framework points of view, these use cases are just slightly different from the scalar value use case. The sole difference is the larger data size but as these larger data packets are infrequently sent, the conclusions are not significantly different from the ones presented in (Paller et al., 2015). One of the more challenging use cases we identified is animal monitoring, specifically rodent tracking . ...
... The GPRS/HTTP is used to send bulk data to the server. (Paller et al., 2015 ) demonstrated that the use of protocols more optimized than HTTP like CoAP does not yield a significant power consumption saving over the GPRS bearer. The SMS infrastructure is employed as the push bearer for server-initiated operations like management operations. ...
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Foreword by Peter Friess & Gérald Santuci: It goes without saying that we are very content to publish this Clusterbook and to leave it today to your hands. The Cluster of European Research projects on the Internet of Things – CERP-IoT – comprises around 30 major research initiatives, platforms and networks work-ing in the field of identification technologies such as Radio Frequency Identification and in what could become tomorrow an Internet-connected and inter-connected world of objects. The book in front of you reports to you about the research and innovation issues at stake and demonstrates approaches and examples of possible solutions. If you take a closer look you will realise that the Cluster reflects exactly the ongoing developments towards a future Internet of Things – growing use of Identification technologies, massive deployment of simple and smart devices, increasing connection between objects and systems. Of course, many developments are less directly derived from the core research area but contribute significantly in creating the “big picture” and the paradigm change. We are also conscious to maintain Europe’s strong position in these fields and the result being achieved, but at the same time to understand the challenges ahead as a global endeavour with our international partners. As it regards international co-operation, the cluster is committed to increasing the number of common activities with the existing international partners and to looking for various stakeholders in other countries. However, we are just at the beginning and, following the prognostics which predict 50 to 100 billion devices to be connected by 2020, the true research work starts now. The European Commission is decided to implement its Internet of Things policy for supporting an economic revival and providing better life to its citizens, and it has just selected from the last call for proposals several new Internet of Things research projects as part of the 7th Framework Programme on European Research. We wish you now a pleasant and enjoyable reading and would ask you to stay connected with us for the future. Special thanks are expressed to Harald Sundmaeker and his team who did a remarkable effort in assembling this Clusterbook.
Conference Paper
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Nodes within existing P2P networks typically exchange periodic keep-alive messages in order to maintain network connections between neighbours. Keep-alive messages serve a dual purpose, they're used to detect node failures and to prevent idle connections from being expired by NAT devices. However despite being widely used, the interval between messages are typically fixed below the timeout value of most NAT devices based upon crude rules of thumb. Furthermore, although many studies have been conducted to traverse NAT devices and other studies seek to improve failure detection in P2P overlay networks; the limitations of NAT devices have received little research attention. This paper explores algorithms which allow nodes to adapt to the timeout values of individual NAT devices and investigates the resulting trade-offs.
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Conference Paper
Always-on applications, such as push email and voice-over-IP, are characterized by the need to be constantly reachable for incoming communications. In the presence of stateful firewalls or NATs, such applications require "keep-alive" messages to maintain up-to-date connection state in the firewall or NAT, and thus preserve reachability. In this paper, we analyze how these keep-alive messages influence battery lifetime in WCDMA networks. Using measurements in a 3G network, we show that the energy consumption is significantly influenced by the radio resource control (RRC) parameters and the frequency of keep-alive messages. The results suggest that especially UDP-based protocols, such as mobile IPv4 and IPsec NAT traversal mechanisms, require very frequent keep-alives that can lead to unacceptably short battery lifetimes.
Article
Recent advances in understanding relationships between spectral reflectance of vegetation canopies and the structural and physiological drivers of canopy-atmosphere carbon dioxide exchange highlight the potential for using narrowband spectral vegetation indices to spatially scale CO2 fluxes beyond the area of a tower footprint. However, ground reference observations of narrowband spectral reflectance in support of satellite observations can be challenging to obtain because (1) automated sampling of both upwelling and downwelling radiation is required over extended time periods to characterize diurnal and seasonal variability, (2) hyperspectral spectroradiometer data and hardware can be sensitive to environmental factors such as temperature and moisture, and (3) hyperspectral spectroradiometers are expensive, greatly limiting prospects for widespread automated sampling. We have therefore developed the QuadPod: a simple, lightweight, relatively low cost and low power sensor capable of continuously measuring upwelling and downwelling radiation in 10 nm wavebands centered at 532 nm, 568 nm, 676 nm, and 800 nm. QuadPod measurements can be combined to calculate spectral reflectance indices (e.g., the photochemical reflectance index, PRI; and the normalized difference vegetation index, NDVI) useful for modeling canopy-atmosphere carbon exchange. The basic QuadPod instrument design described here can be implemented using any combination of optical filters in order to calculate other spectral vegetation indices.