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A prototype design of a smart and portable coastal fisheries assistant system

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This paper designs a portable fisheries assistant system, capable of detecting operation zone within marine protected areas and recording trajectory. The microdevice used to deploy this system has enough computational powers to achieve the above tasks and can integrate with external modules, i.e., GSM transmitter and receivers, GPS receivers, and external storages. Microdevices require much less energy than regular computers and can be activated using mobile power banks, which makes it suitable to carry on fishing rafts and sampans which do not have a stable source of electric power. Development of the software will also take account of using operations that consume less power to lengthen the operation time of the fisheries assistant system. The development of the current stage will use 4G mobile network to relay information and will be field tested by going outside and on to the seas. To support the system, a control center will be established to receive, store, process, and integrate the data sent by the assistant system for further processing.
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A prototype design of a smart and portable coastal
fisheries assistant system
Jing-Chun Luo1, Hsin-Yu Tsai1, Min-Hsuan Lu1, Shin-Yu Wang1, Wei-Hsiang Hung1, and William W.Y. Hsu12
1Department of Computer Science and Engineering, National Taiwan Ocean University,
Keelung, Taiwan 202
2Corresponding Author
Email: wwyhsu@ntou.edu.tw
Abstract: This paper designs a portable fisheries assistant system, capable of detecting operation zone within marine protected
areas and recording trajectory. The micro device used to deploy this system has enough computational powers to achieve the
above tasks and can integrate with external modules, i.e., GSM transmitter and receivers, GPS receivers, and external storages.
Micro devices require much less energy than regular computers and can be activated using mobile power banks, which makes it
suitable to carry on fishing rafts and sampans which do not have a stable source of electric power. Development of the software
will also take account of using operations that consume less power to lengthen the operation time of the fisheries assistant system.
The development of current stage will use 4G mobile network to relay information and will be field tested by going outside and
on to the seas. To support the system, a control center will be established to receive, store, process, and integrate the data sent
by the assistant system for further processing.
Index terms: Fisheries assistant system, Coastal fisheries, Microdevices, GPS
I. INTRODUCTION
Taiwan is an island country surrounded by water, with
fisheries industries producing an estimate of 86 billion TWD
in 2016 [1]. Overseas fisheries rank first in the amount of
produce, inland aquaculture ranks second, and offshore fish-
eries (fishing activities involving within Taiwan’s exclusive
economic zone (EEZ)) and coastal fisheries (fishing activities
within 12nm territorial waters of Taiwan) totals in third place
(see Table I). The size of Taiwan’s fleet is also incredi-
ble as compared to the island size, with a total of 12381
powered vessels and 10109 un-powered fishing rafts and
sampans [1]. How to effectively manage Taiwan’s large fleet
and marine resources have been important since 1960’s. As
marine resources are renewable, it is not infinite. Overfishing
may damage the long-term sustainability of fish stocks and
cause either direct or indirect consequence arising from the
modification of ecosystems [2][3] and international conflicts
regarding resource management [4].
Illegal, unreported and unregulated fishing (IUU) is a major
threat not only to Taiwan’s fisheries but also to global marine
resources as overfishing destroys the livelihoods of many
communities who depend on fisheries. It is estimated that each
year, between 11 and 26 million tonnes of fish are caught
illegally, corresponding to at least 15% of world catches. Its
global value reaches up to 10 billion euros per year. As the
world’s largest importer of fisheries products, the European
Commission (EU) has adopted a firm stance against illegal
fishing worldwide. No access of fisheries products is allowed to
the EU market unless they are certified as legally fished. Such
trade sanctions are currently in place for Cambodia, Guinea,
and Sri Lanka, which received a red card from the European
Commission (EUC).
Illegal, unreported and unregulated (IUU) fishing is not a
new phenomenon in capture fisheries nor is it confined to high
seas fisheries. It also occurs in the exclusive economic zones
(EEZs) of coastal States by national and foreign vessels and
river and inland fisheries. However, in marine fisheries, while it
is difficult to estimate precisely the total IUU catch in tonnage
or value terms, the level of IUU fishing has reached significant
proportions for some species. These catches, in many cases,
are being made by both authorized and non-authorized fishers,
i.e., the catches are not being taken only by vessels operating
under ’flags of non-compliance’ (FOC).
The Fisheries Agency, Council of Agriculture, Executive
Yuan of Taiwan, in the purpose of detecting unauthorized or
illegal application for offshore and coastal fishing vessel fuel
stipend and future marine resource management, has developed
the Voyage Data Recorder (VDR) system in 2006. After a year
of research, development, prototyping, testing, and onboard
evaluation, the Fisheries Agency has finally regulated that all
fishing vessels in Taiwan must be equipped with the VDR
system. The VDR system has to be installed on vessels with
power generators for it to operate. However, many of the small
fishing rafts (see Figure 1) and sampans (see Figure 2) are
driven by outboard motors install of a full engine, do not have
any source of electric power. To compensate for these vessels,
the Fisheries Agency has developed a portable version of the
VDR which runs on pure battery power.
Current technology advancements made it possible to en-
hance the VDR devices, allowing it to provide information
aside from only keep tracking of trajectory data. In this paper,
we will discuss a prototype system, a portable coastal fisheries
assistant system (FAS), which not only keeps track of any
fishing vessels but also providing it with fruitful information
to assist fishers in their fishing operations.
Fig. 1. A PVC raft. This raft is made out of PVC pipes and can carry very
limited cargo.
Fig. 2. A sampan2.This type of vessels is generally used for small or
family-scale fisheries.
II. BACKGROUND AND RELATE D WOR KS
Taiwan has established marine protected areas (MPAs) to
protect ocean resources and environment, preserving wildlife
biodiversity, and ensure sustainable developments. According
to different laws, i.e., fisheries law, national park law, cultural
asset preservation law, and tourism development law, MPAs in
Taiwan has been classified into three level. The highest level
prohibits entering and influencing the region, which makes the
whole area off limits. The second level prohibits harvesting,
where people can still enter the region for leisure. The last
level is limited access MPAs, where harvesting is allowed but
with quota limits. The total area of Taiwan’s MPA within 12
nautical miles territorial water is approximately 30 thousand
square kilometers, accounting a 47.5% of the total area. The
TABLE I. Taiwan fisheries industry production in 2016. OVERS EA S
FIS HER IES C ON TRI BU TE TO N EAR LY HAL F OF TAI WANS FI SHE RY INC OM E.
Sector Production Value
(Thousand NTD)
Overseas 37,714,515
Offshore fisheries 10,641,077
Coastal fisheries 4,114,796
Inland fisheries 6,265
Offshore aquaculture 5,601,349
Inland aquaculture 28,374,596
Total 86,452,598
MPAs are updated by the government and information may not
successfully reach every fisher. Thus one of the missions of this
system is to notify the fishers that they are in a restricted fishing
zone. In addition, some of the vessels may travel too far and
intrude exclusive economic zones (EEZ) of other countries.
They should also be alerted that they are not within allowed
fishing waters.
Fishery activities within the territorial waters are usually
family and small-scale fisheries. Over half of the vessels,
i.e., fishing rafts and samples, are equipped with outboard
motors only and are too small to have electric power gener-
ators installed. This makes VDRs obsolete, and the solution
is to develop similar, self-sustaining small devices which
have batteries included. The development of such device, a
portable coastal fisheries assistant system (FAS), can provide
great value. For example, Aswani and Lauer show that GIS
can be used to incorporate sociospatial information such as
indigenous knowledge and artisanal fishing data to establish
marine protected areas (MPAs) [5]. The combination of spatial
tools and anthropological fieldwork into sociospatial systems
helps researchers design and implement resource management
strategies. Using the GIS systems to create habitat maps has
been done by Monk et al. [6]. The gear used by Monk et al.
is waterproofed and thus the data gathering process can be
done by scuba divers, which allows accurate mapping of the
subtidal zones of shallow temperate reef systems using less
budget. By using the FAS, we can understand the activities of
these small-scale fisheries and the relation between their social
impact and the environment.
III. SYS TE M DES IGN
The infrastructure set up for the fisheries assistant system
is shown in Figure 3. We choose to use a Raspberry PI device
as our backbone due to its small and powerful computation
ability. The system can be developed and downloaded onto
an SD memory card, which can then use to boot the FAS.
Since this device is aimed for offshore and coastal fisheries
activities, we choose to use GSM and WIFI as our primary
communication method. When the device is carried of the
vessels and back on land, WIFI (or even using a wired internet)
can be used to transfer software and database updates. Two
modes of GPS position transfer methods must be provided on
the FAS. When GSM is available, all information including the
GPS position is transferred in real time. If the vessel moves out
of range, the FAS will store the information in the memory,
wait for the connection to be re-establish, and then resume
data transfer. All of the data will be relayed to a central control
center for recording and further analysis, i.e, trajectory analysis
[7] and catch analysis and behavior [8].
The software design follows the flowchart in Figure 4.
The required databases are processed and stored on the SD
card. After the system is booted, it continuously accepts GPS
strings from the GPS IC. Not all strings are valid due to
some environmental condition, i.e., obscuring, electromagnetic
interference, and thus each GPS string must be checked with
the checksum provided. Following, the GPS position is used
to find which region is the vessel in, either an MPA, an EEZ,
or none (at high seas). The GPS is also recorded in internal
memory. If a network connection is present, either GSM or
WIFI, the position will be transmitted in real time to the central
Fig. 3. Framework of the fisheries assistant system. The fisheries assistant system can be connected to the network to transmit and receive data.
control station. Otherwise, the vessel must be out of range from
any communication stations, GPS position transmissions will
be delayed until a network environment is established.
Fig. 4. Software flowchart of FAS. The FAS has more than enough internal
memory to store external data and gathered data for delayed processing.
TABLE II. Field in the VDR sample. THE FI ELD S IN O UR VD R
SA MPL E IS D EFIN ED US IN G NMEA STAN DAR DS (OB TAIN ED F ROM [9]).
Field Comment
$GPRMC Recommended Minimum sentence C
033416.00 Fix taken at 03:34:16.00 UTC
A Status A=active or V=Void
2619.06271,N Latitude 26 degree 19.06271’ N
11952.82288,E Longitude 119 deg 52.82288’ E
4.059 Speed over the ground in knots
198.65 Track angle in degrees
120514 Date 2014/05/12
,,,A Magnetic Variations and “Unknown”
*6D The checksum data, always begins with *
A. GPS data
The GPS position can be obtained by adding a GPS
module3to the Raspberry PI. This GPS chip can generate
3We choose to use the VK2828U7G5LF GPS IC for our prototype system.
standard NMEA (National Marine Electronics Association)
format strings [9]. An example string from our system is
$GPRMC,033416.00,A,2619.06271,N,11952.82288,
E,4.059,198.65,120514,,,A*6D
Detailed field definition is given in Table III.
TABLE III. Field in the VDR sample. THE FI ELD S IN O UR VDR
SA MPL E IS D EFIN ED US IN G NME A STAN DAR DS (O BTAI NED F ROM [9]).
Field Comment
$GPRMC Recommended Minimum sentence C
033416.00 Fix taken at 03:34:16.00 UTC
A Status A=active or V=Void
2619.06271,N Latitude 26 degree 19.06271’ N
11952.82288,E Longitude 119 deg 52.82288’ E
4.059 Speed over the ground in knots
198.65 Track angle in degrees
120514 Date 2014/05/12
,,,A Magnetic Variations and “Unknown”
*6D The checksum data, always begins with *
GPRMC strings use the degree (D) and minutes (M) for
longitude and latitude representation. We have converted this
representation into decimal degree (DD) representation for ease
of access in databases using
DD =D+M
60 .
The raw data acquired has a precision up to five decimal places,
indicating that the maximum accuracy of the minute field can
be 0.00001
60 = 0.00000016, up to a precision of 6 digits in
decimal degree representation. The GPS is precise to 11.132cm
at the equator and 4.3496cm at 64N/S. This conversion is
adequate since the accuracy of GPS is around 7.8 meters at
a 95% confidence interval4. When storing information in our
database, the truncation of the decimal degree to 6 decimal
digits would not generate any bias under this supporting fact.
B. MPA and EEZ detection
The second type of data is geo-referenced data which
includes MPA regions and EEZs. EEZ information is acquired
from [10] and MPA information is downloaded from the Fish-
eries Agency of Taiwan [1]. MPAs defined in this document
4Source: http://www.gps.gov/systems/gps/performance/accuracy
is divided into three categories: artificial reef protected area,
gemstone coral protected area, and the protected reef area.
Figure 5 shows MPAs of Taiwan around Keelung area. These
data are not always provided as a polygon defined region (as in
Ain Figure 5). MPAs may be announced as a circular region,
given a coordinate Pas the center and rnautical miles as
radius (as in Bin Figure 5), or it may be declared as a capsule
shape region by defining a line Land a distance to the line d
(as in Cin Figure 5). Moreover, the regions may overlap as
in Din Figure 5.
Fig. 5. MPAs of Keelung coast. Areas in grey are artificial reef protect area
and areas in blue are natural reef protected areas. MPA shapes may be either
a circle, a capsule shape, or any polygon shape.
Detecting proximity of a GPS point to an MPA does not
always have to be done with a general point in polygon
algorithm. We can take advantage of the degenerated repre-
sentations, point plus radius and segment plus radius, of an
MPA. The first case point plus radius can be computed using
Algorithm 1. A simple radius test can identify if the point is
within the MPA or not. Algorithm 2 is used to compute the
segment plus radius case. It is a little more complicated as it
requires the use of the laws of cosine.
Algorithm 1 MPA region type: Point
Input: GPS position of the vessel P(x, y), MPA center
A(x, y), and radius of the MPA r;
Output: Is P(x, y)within the MPA;
1: for all P(x, y)gathered by the GPS do
2: Read the MPA data given as a point A(x, y)and radius
rfrom the database;
3: Compute the distance dof P(x, y)to A(x, y);
4: if d < r then
5: return P(x, y)is within a MPA;
6: else
7: return P(x, y)is not in a MPA;
8: end if
9: end for
Algorithm 2 : LineString
Input: GPS position of the vessel P(x, y), MPA segment
points A(x, y)and B(x, y), and the distance rcovered
from AB;
Output: Is P(x, y)within the MPA;
1: for all P(x, y)gathered by the GPS do
2: Read the MPA data given as a line A(x, y)and
B(x, y)from the database;
3: Compute the distance dAof P(x, y)to A(x, y);
4: Compute the distance dBof P(x, y)to B(x, y);
5: Compute minimum distance dMof Pto segment AB
using the distance of AB,dA, and dB;
6: if dM< r then
7: return P(x, y)is within a MPA;
8: else
9: return P(x, y)is not in a MPA;
10: end if
11: end for
IV. EXPERIMENTS
We have used the Raspberry PI 3 Model B+ along with a
VK2828U7G5LF GPS IC, 64G SD memory card, and supplied
with one Panasonic 18650 lithium ion battery with 3400 mah
capacity. Figure 6 the front view of the FAS system. For the
purpose of testing and ease of viewing, we used a large 7-
inch touch display. It is expected to be replaced with a smaller
display to conserve power in the future. The rear of the FAS
system contains the Raspberry PI mounted to the display, a
GPS IC connected to the Raspberry PI through general purpose
input output (GPIO) pins, and a portable battery pack. This
battery pack can hold up to a maximum of for 18650 lithium-
ion batteries. The prototype FAS system has been taken out
for testing and it can compute MPA and EEZ regions in real
time. A quadtree data structure has been used to speed up
computation but details are out of the scope of this paper. For
areas which are currently unreachable by our design team, we
have a simulator mode to input artificially generated GPSpoints
to test the results. Trajectory records are done with government
regulations currently set to 3 minutes interval. By allocating
1G memory from the SD card, the device can record more
than 70 years of GPS information. With one battery, field test
results show that this system can last up to 2 hours with the
display on at all times.
V. DISCUSSIONS
The FAS proposed in this paper is an ongoing prototype
system. It is portable and very flexible as it is designed from a
microcomputer which can be generally programmed. However,
many improvements can still be done. First is the power
consumption. We have used a 7-inch touch display which can
be replaced by a smaller display or even electronic paper [11].
Second, we can incorporate fisheries data showing catches
within the area. Third, if the device is within range, weather
data or warning can be issued to each device. Fourth, these
devices are to be taking out on the sea and may need to operate
for a long period of time, thus increasing the battery capacity
and provide waterproofing mechanisms is important.
From the management perspective, the deployment of
FAS allows authorities to understand the behavior of these
Fig. 6. Front view of the FAS prototype. The prototype is equipped with
a 7-inch touch display and an external battery pack.
Fig. 7. Rear view of the FAS prototype. The GPS is connected through
the GPIO pins of the Raspberry PI.
small-scale fishery vessels, which are practically “invisible”
to current monitoring policies. This data will help officials
and researchers understand the resource usage and activity
patterns in developing sustaining measures for the environment
of coastal waters.
ACK NOW LE DG ME NT
The authors are supported in part by the Ministry of
Science and Technology of Taiwan, under grant MOST-106-
2221-E-019-071 and fully supported by the Council of Agri-
culture, Fisheries Agency of Taiwan under grants 107AG-
9.1.5-FA-F1(1-1) and 107AG-9.2.3-FA-F1(4). This research
has no affiliations with or involvement in any organization or
entity with any financial interest or non-financial interest in
the subject matter or materials discussed in this manuscript.
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Fig. 8. Prototype system display. FAS is connected to a touch screen
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Standard for Interfacing Marine Electronics Devices, National Marine Electronics Association
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