=Paper=
{{Paper
|id=Vol-2731/paper02
|storemode=property
|title=Assessment of mobile phone applications feasibility on plant recognition: comparison with Google Lens AR-app
|pdfUrl=https://ceur-ws.org/Vol-2731/paper02.pdf
|volume=Vol-2731
|authors=Zhanna I. Bilyk,Yevhenii B. Shapovalov,Viktor B. Shapovalov,Anna P. Megalinska,Fabian Andruszkiewicz,Agnieszka Dołhańczuk-Śródka
|dblpUrl=https://dblp.org/rec/conf/aredu/BilykSSMAD20
}}
==Assessment of mobile phone applications feasibility on plant recognition: comparison with Google Lens AR-app==
https://ceur-ws.org/Vol-2731/paper02.pdf
61
Assessment of mobile phone applications feasibility on
plant recognition: comparison with Google Lens AR-app
Zhanna I. Bilyk1[0000-0002-2092-5241], Yevhenii B. Shapovalov1[0000-0003-3732-9486],
Viktor B. Shapovalov1[0000-0001-6315-649X], Anna P. Megalinska2[0000-0001-8662-8584],
Fabian Andruszkiewicz3[0000-0001-5318-3793] and
Agnieszka Dołhańczuk-Śródka3[0000-0002-9654-4111]
1 National Center “Junior Academy of Sciences of Ukraine”,
38/44 Dehtiarivska Str., Kyiv, 04119, Ukraine
2 National Dragomanov Pedagogical University, 9, Pyrogova Str., Kyiv, 01601, Ukraine
3 Uniwersytet Opolski, 11a Kopernika pl., Opole, 45-040, Poland
zhanna_bio@man.gov.ua
Abstract. The paper is devoted to systemizing all mobile applications used
during the STEM-classes and can be used to identify plants. There are 10 mobile
applications that are plant identifiers worldwide. These applications can be
divided into three groups, such as plant identifiers that can analyze photos, plant
classification provides the possibility to identify plants manually, plants-care
apps that remind water of the plant, or change the soil. In this work, mobile apps
such as Flora Incognita, PlantNet, PlantSnap, PictureThis, LeafSnap, Seek,
PlantNet were analyzed for usability parameters and accuracy of identification.
To provide usability analysis, a survey of experts of digital education on
installation simplicity, level of friendliness of the interface, and correctness of
picture processing. It is proved that Flora Incognita and PlantNet are the most
usable and the most informative interface from plant identification apps.
However, they were characterized by significantly lower accuracy compared to
Google Lens results. Further comparison of the usability of applications that have
been tested in the article with Google Lens, proves that Google Lens characterize
by better usability and therefore, Google Lens is the most recommended app to
use to provide plant identification during biology classes.
Keywords: mobile application, STEM-classes, augmented reality, plant
identification, Google Lens.
1 Introduction
To date, the introduction of a mobile phone into the educational process is a modern
instrument to achieve better results. The usage of a mobile phone during classes allows
visualization of educational material, involving students in research, which increases
students’ motivation for learning [20; 26]. Mobile phone applications compared to
computer approaches are characterized by the most promising advantages including
mobility of usage, possibility to use both internal and external sensors (not commonly
___________________
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0).
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used). The modern educational directions include personalization of research process
which may be achieved by using mobile phones [25]. However, it was proved that not
elements of education led to high efficiency but a general didactic approach during
which it was used. The main concept during which the mobile approach relevant to use
is STEM/STEAM/STREAM technology. It includes elements of both research and
engineering which can be based on the use of computer software or mobile applications.
1.1 Types of educational software
All software that can be used during the learning process in the application of STEM
technology can be divided into desktop applications, mobile applications, and web-
oriented technologies. There are a lot of scientific papers related to ways of ICT
implementation during STEM-based classes. The most interesting of them are
providing of augmented reality [2; 21; 26; 27; 29; 30; 33; 37], virtual reality [3; 14; 16;
20; 23; 24; 31; 32; 35; 45], providing of digital environments of education, including
computer modeling [7; 19; 34; 36; 40;], providing of centralized educational networks
[38; 41; 43], mobile-based education [18; 22; 27; 28; 33], modeling environments [4;
8; 9; 12; 17] providing of education visualization by including YouTube videos [6], 3D
modeling [5], and printing [15], etc. Comparisons of the most used in the education
process software are presented in table 1.
Table 1. Comparisons of the most used in the education process software.
Type Web-oriented Mobile applications Desktop applications
Instal- From official stores or From official stores or ins-
Not needed
lation using application file tallation files
Compatible version of
General Compatible version of And-
Compatible Internet browser Windows / macOS / Linux
require- roid, iOS or another mobile
for all feathers support or another desktop opera-
ments operating system
ting system
Modeling, calculation, vi-
sualization, video presen- Modeling, calculation, vi-
Faciliti- Modeling, calculation, visua- ting, measuring using both sualization, video presen-
es lization, video presenting internal and external sen- ting, using additional ex-
sors, photo analysis, AR, ternal sensors
VR
Main Cross-platforming, no instal- Stability, huge spreading,
Huge facilities, mobility of
advan- lation required, low device and variation of applicati-
usage
tages space usage ons
Limited opportunities, may
Main Lack of individualization,
not start correctly depending
disad- Needs technical updates the lesser effect of increa-
on the platform and technical
vanta- which may be expensive sing motivation during
characteristics, lack of in-
ges STEM-education
dividualization
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As shown on the table, one of the most perspective to use in education is the mobile
application due to their multi-capabilities, interaction with students in their research
and visualization on the educational process. Nowadays a lot of pedagogical researches
is related to analyzing approaches mobile phone applications can be used during the
educational process. In general, based on the facilities, it is possible to provide a
classification of mobile application on those which provides measuring, analyzing, the
image recognizing and its classification, providing course education, VR, and AR-
based. We offer to structure training applications that can be installed on a student's
mobile phone into the following categories, such as:
─ training platforms;
─ meter applications;
─ video analysis apps;
─ applications that analyze images and classify them;
─ augmented reality (AR) and VR apps.
Comparisons of different mobile apps categories are shown in table 2.
Table 2. Comparisons of different mobile apps categories.
Type of
Description Examples
application
These platforms allow the teacher to
create instructional content, Google Classroom, Prometheus,
Education platforms communicate with students, give them Coursera, Microsoft Office 365
assignments and check them out for Educational
automatically
Measure, AR-ruler, Smart
Measuring These sensors and their software are Measure, Lux-meter,
applications already built into mobile phones Accelerometer, Magnet Field
Meter
It allows you to measure distances,
Image analysis apps angles, perimeters, areas, and ImageMeter
calculate with this data.
Image recognizing Google Lens, Photo Sherlock,
These mobile applications allow you
and it’s Plant Net Identification,
to identify species of plants and
classification Mushroom, Identify, Shazam,
animals using photos
applications Dog Scanner, Identify Anything
VR and AR-based Allow virtual travel, get a spatial Minecraft Earth, IKEA Place,
apps image of the training material. Ideofit, Lego Hidden Side
We can distinguish some smartphone apps which give the highest potential to
increase motivation and integration with providing investigation, especially in biology,
which is apps-identifiers. Today, there is a range of mobile applications that identify
wildlife. These supplements can identify insects (for example, Insect identifier Photo),
animals (Dog Scanner), and plants (Flora Incognita, PlantSnap, Picture This). Some
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applications identify both plants and animals, for example, Seek. In our opinion, most
perspectives are applications that provide analyzing of the static its nature objects
(plants) due to the photographic process don't require highly expensive smartphones to
obtain sufficient quality photography to provide analysis. Therefore, this approach can
be used widely during the educational process, almost in all schools.
1.2 The problem of plants identification
There are about 27,000 species of flora in Ukraine, such biodiversity requires detailed
description and study. Also, natural conditions are constantly changing, and this causes
changes in the species composition of biocenosis. Both aspects indicate that there is a
problem with plant identification. One of the basic principles of pedagogy is the
principle of a nature experiment. So, training should be carried out in an environment
where the mobile phone should become a full-fledged learning tool.
Some apps can be installed on the student's mobile phone for free to determine the
species of plants, their morphology, the range of distribution, and more. In our previous
research, it was found that Google Lens characterized by very high accuracy of
identification, especially on trees and shrubs [39]. Taking to the account simplicity of
the application and its dissemination, there some papers and devoted to describing and
researching Google Lens [10; 11; 42]. Google lens can provide analysis of real-life
objects in AR and provide additional information neural networks algorithms.
However, other applications can be used to provide identification and these applications
may be more specialized. Therefore, they can provide more accurate analysis because
their database consists only of plants images which can decrease the number of false
detections, and apps can provide more correct process of plant identification and
inputting the information (requesting from the user to input different parts of plants).
Despite the great specialization of other applications, we hypothesize that Google
Lens is the best plant analyzer due to the large selection of plants and the existence of
a special application for teaching it to a large number of people – Google Crowdsource
(500 000+ installation).
Therefore, the purpose of this article is to analyze existing applications that can be
used in teaching biology both in the classroom and in the field.
There are about 10 applications that can be used to identify the plants. Most common
of them are LeafSnap, Seek, PlantNet, Flora Incognita, PlantSnap, Picture This, Florist-
X (in Russian), What is a flower (in Russian), Manager of houseplants (in Russian).
These applications can be divided into three groups, such as:
─ plant identifiers that can analyze photos (Google Lens, for example, PlantNet, Flora
Incognita, PlantSnap, Picture This.
─ plant classification provides the possibility to identify plants manually. The plant’s
classificatory commonly contains pictures and information about plant kind. But the
quality of analysis, in this case, will depend on the user's knowledge and skills which
may be hard for both teachers and students. Their use in biology lessons within the
STEM approach has considerable potential because it allows for interesting and
rapid acquisition of plant morphology. However, it works like an interactive book
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that can interact with students lesser than apps of the first type (for example, Florist-
X and What is a flower).
─ plants-care apps that remind water of the plant or change the soil, which by the lower
potential compared to other types of application (for example Manager of
houseplants).
Taking into account all advantages of plant identifiers, it was used as an object of the
research. The analysis of the general view is shown below.
Flora Incognita. According to the developer, the application can identify 4800
species of plants. Before the analysis user chooses plant type (flower, tree, grass). The
process of analyzing requests photographs of different plant parts. After determining
the species, it links to Wikipedia and the site www.plantarium. A general view of the
application interface is presented in figure 1.
Fig. 1. Flora Incognita interface.
PlantNet. According to the developer, this application can identify 21,920 species of
plants. It contains headings: flora of the world (very broad heading Western Europe,
USA, Canada, Central America, Caribbean islands, Amazon, French Polynesia), useful
plants, invasive plants, weeds. The user can confirm the particular plant, i.e. the
program is being trained. When determining the part of the plant (root, shoot) is
indicated. There are photos by family and you can determine by family, the principle is
the determinant.
There is no connection with other information resources, information about the
species is very limited (only photo and Latin name). A general view of the application
interface is presented in figure 2.
PlantSnap. According to the developer, this application can identify 585,000
species of plants. Need to create a profile. This can be done using Facebook, almost
Gmail Google. Detailed instructions come to the user's mail. It contains instructions
with English voice and Russian subtitles. You get a photo and the program offers
several options. You can also use images you already have in the gallery. When you
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define a program, you save, that is, confirm. It contains a ribbon where each corset can
post and comment. There are no links to other resources, only the photo and the Latin
name of the plant. PlantSnap limits identifications by 25 plants per account per day A
general view of the application interface is presented in figure 3.
Fig. 2. PlantNet interface.
Fig. 3. PlantSnap interface.
PictureThis. According to the developer, this application can identify 10,000 species
of plants. During authorization, prompts to enter a bank card immediately, if the user
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does not, offers a free version. The user points the camera and the program determines
the species, under the name of the species is given a botanical description, an interesting
fact about the plant. There are plants that you cannot identify yourself, sent by other
users, that is how the program learns. A general view of the application interface is
presented in figure 4.
Fig. 4. PictureThis interface.
LeafSnap. The user takes a picture of the plant, indicating which part of the plant it is.
And then he chooses the most similar look in the photos. The botanical description of
the plant is given under the name of the species. A general view of the application
interface is presented in figure 5.
Fig. 5. LeafSnap interface.
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Seek. It contains instructions, offers INATURALIST authorization, but can be operated
without authorization. Immediately determines the geographical location of the user,
sets the rules of safety in the wild. The mobile application provides clear, concise
instructions for each stage of the study. For each activity the participant gets achieves
that is motivation to learn. The app invites you to participate in nature research projects.
A general view of the application interface is presented in figure 6.
Fig. 6. Seek interface.
2 Methods of analyzing
To provide analysis on the usability of applications related to plant identification, a
survey of experts on digital didactics was provided. The main criteria were installation
simplicity, level of friendliness of the interface, correctness of picture processing. Each
criterion was evaluated from 0 to 5 (as higher than better). Those applications which
were characterized by average evaluation more than 4 were used to further analysis on
quality of identification due taken to account fact usage of the application during the
educational process, where it will be used by students and teachers, both potentially
with not the highest level of ICT competence.
Analysis of quality of identification was provided by a simplified method compared
to our previous research [34] due aim of this paper to obtain general state on application
plant identification accuracy. To provide it, 350 images from the list of plants of the
“Dneprovskiy district of Kiev” were taken to provide analysis. The key from the
“Dneprovskiy district of Kiev” plant classification was used as control. To provide an
evaluation table for each application was used. For each correctly defined type of
application received 1 point (see an example in table 3).
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Table 3. Example on the table of apps analyzing.
The name of the plant Flora Incognita PlantNet
Prunus armeniaca (Apricot) 0 0
Jasione montana 0 1
Ageratum houstonianum 0 1
Chaenomeles japonica 0 0
Amaranthus 1 0
Ambrosia artemisiifolia 0 1
Amorpha fruticosa 0 0
Anemo 1 1
Anemonoides ranunculoides 1 0
Anisanthus tectorum 0 0
Finally, all obtained results, including both, general usability evaluation (survey) and
results on identification quality were compared with results on Google Lens to
summarize information and achieve a general and final state in this field.
3 Results
3.1 Analysis of application identification accuracy
To compare mobile applications, it is important to explore the algorithm for identifying
plants.
According to botanical science, the algorithm for determining a plant includes:
establishing the life form of the plant (tree, bush, grass); then studying the vegetative
parts of the plant (leaves, stem). Generally speaking, generative organs (flower or fruit)
analysis is often required to establish a specific species name. Geographic location is
very important to identify many species. For example, Picea omorika and Picea abies
are very similar species, but Picea omorika only in Western Siberia and Eastern Bosnia
and Herzegovina. If the algorithm for determining the plant in the application includes
the definition of life form, photographing the vegetative and generative organs, as well
as the geographical location of the object, then we consider such an algorithm
completely correct. If the application of plant identification is based on photographs of
different organs of the plant, such an algorithm is correct. If the application of the plant
is based on the analysis of one image in one click, then this is a simple algorithm. The
educational process needs to have links to other sources.
The results of comparing mobile applications that can analyze plant photos are
shown in table 4.
PlantNet is the easiest app to install. Also, pretty easy to install are LeafSnap and
Flora Incognita. Apps LeafSnap, Flora Incognita, and Seek to have the simplest
interface. PlantSnap, PictureThis, and PlantNet are characterized by the most
uncomfortable process of identification which can be complicated for teachers. Results
of detailed analyses on plant identification applications are presented in figure 7.
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Table 4. The results of comparing mobile applications that can analyze plant photos.
Amount of Correctly process of Communication with other
the plants analyzing information services
Contains links to Catalogue of Life,
Plants for a Future and Wikipedia.
Flora 4800 (only The analysis algorithm is
Flora Incognita with Russian
Incognita German) correct
interface provides links to the
Russian site www.plantarium.ru
Only the name of the plant. Includes
elements of social networks (by
The analysis algorithm is
PlantNet 21920 sharing plants student found and
completely correct
subscriptions). It contains links to
Wikipedia.
The analysis algorithm is Own description. Provides
PlantSnap 585000
simple. searching on amazon to buy
Provides very structured
The analysis algorithm is information (including type,
PictureThis 10000
simple. lifespan, height, flower diameter),
care aspects, usage of the plant
The analysis algorithm is
correct. After determining,
No Contains links to Wikipedia,
the collection of photos of
LeafSnap information Pl@ntUse, Global Biodiversity
this plant in different
available Information Facility
conditions (healthy and
unhealthy) is possible to use.
The analysis algorithm is the
No Has no detailed description, but
simplest.
Seek information propose “species nearby in this
For identification users get
available taxon”
archives
6
5
Ammont of points
4
3
2
1
0
PlantNet PlantSnap PictureThis LeafSnap Seek Flora
Name of appication incognita
Installation simplicity
Level of friendliness of the interface
Fig. 7. Results of detailed results on plants identification applications usability analysis.
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In general, LeafSnap, Flora Incognita, PlanNet are the most usable. However, the total
number of points each of the applications received is presented in figure 8.
4.5
4
3.5
Ammont of points
3
2.5
2
1.5
1
0.5
0
PlantNet PlantSnap PictureThis LeafSnap Seek Flora
incognita
Name of appication
Fig. 8. Integrated results on the usability of plants identification applications.
Flora Incognita provides correct identification of 71% of plants compared to 55%
provided by PlantNet. For comparison, this figure for Google Lens is 92.6%. In our
previous work, we demonstrated that Google Lens does not differentiate native species
from Ukraine. It seems like PlantNet provides the same Google Lens searching only in
international resources, unlike Flora Incognita which provides searching at Russian
web-site (in case choosing of Ukrainian region). This may explain a higher percent of
identification accuracy of Flora Incognita, compared to PlantNet. The comparison of
Google Lens with Flora Incognita and PlantNet identification quality is presented in
figure 9.
100
Percent of correct
identifcations, %
80
60
40
20
0
PlantNet Flora incognita Google Lens
Name of the appication
Fig. 9. Results on analysis quality of apps which is identified plant.
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So, Google Lens is characterized by the highest quality of analysis which may be due
to the better recognition algorithm and the most trained neural network. However, it
still may be relevant to use other applications in case it will be characterized by
significantly higher parameters of using. To evaluate this, a similar survey as used for
other plant identification applications was used for Google Lens. Google Lens has the
most intuitive interface, is the most easily loaded, and gives the most accurate definition
result and therefore is characterized by the highest general evaluation. A comparison of
the total points scored by the experts is presented in figure 10.
5
4.5
4
Ammont of points
3.5
3
2.5
2
1.5
1
0.5
0
PlantNet Flora incognita Google Lens
Name of the appication
Fig. 10. Integrated results of usability level of PlantNet, Flora Incognita and Google Lens.
Therefore, Google Lens is the most recommended app to use. Talking to account,
results of usability analysis, and quality of analysis, for those students and teachers who
do not like Google Lens app, it is possible to use Flora Incognita, but PlantNet can’t be
recommended to use due low accuracy which may provide up to half of incorrect
analyzing results.
3.2 Specific features of the applications to use in your own research
Despite the disadvantages, some features of depiction are worth note. Some
applications have their own approach to provide complex research of nature. Those
features are very useful to increase the motivation of students to research nature. The
most interesting approaches to increase motivation provided by PlantNet and Seek.
Dispute negative results on Interface (for Seek, only 3,6 points) or for identification
(for PlantNet, only 55 % of correct identifications), the approaches used to increase
motivation are worth noting.
PlantNet approach.
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One of the features worth note about on PlantNet is the social network it is based on. It
consists of a feed of pictures shared by users of PlanNet. The information in the feed is
devoted to classes “identified”, “unidentified”, and there is a function to display all
information (by choosing “All”). The items in feed with an “identified” filter will
display already identified plants by users and “unidentified” will display not-identified
pictures updated by users. The most perspective is using “unidentified” feed which may
be useful in a few cases:
─ To solve problems with a plant which is hard to identify students have.
─ To train own identification skills by providing identification of pictures of others.
─ To share thoughts in the field of botanic, communicate with other researchers, and
to provide social science networking.
Seek and iNaturalist complex.
The Seek-identification app provides a significantly different approach to increase
students' motivation. It provides achieves for each plant students found which motivates
students to get new and new researches from time to time. The effect of achievement
affects the brain as exaltation and people want it again and again. This is used in games
to motivate students to play again [1; 13; 44]. In the case of Seek, some factors will
motivate students to research nature.
Students who use Seek can integrate it with iNaturalist application (developed by
California Academy of Science and National Geographic). Which gives to students and
teachers powerful systems of different instruments. The first instrument to motivate is
personal journals. This feature gives to student’s possibility to provide own
systematical journals. The general view of personal journal and info card on a single
plant is shown in figure 11.
a b
Fig. 11. The general view of a personal journal (a) and info card on a single plant (b).
74
The iNaturalist propose observing of plants and animals kinds student can find nearby.
This feature is activated by the “Exploring All” function and choosing “My location”.
Also, based on location students can use Missions which provides quests for students
to do, for example, to find “Rock Pigeon”. So, students can observe nature nearby in
general to study it and the program will stimulate students by completing the missions.
The Exploring All and Missions functions are presented in figure 12.
a b
Fig. 12. The Exploring All (a) and Missions functions (b).
a b
Fig. 13. The interface of the projects menu (a) and concrete project (b).
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The program provides collaboration by providing projects. Users can find and chose
projects they like and join be involved in them. It’s worth note, that the app is very
widespread and there are even projects in Ukraine. The interfaces of project selection
and concrete project interface are presented in figure 13.
4 Conclusion
1. Apps related to plant identifications can be devoted to those which can analyze
photos, devoted to manual identification and apps devoted to plant care monitoring.
2. It is proved that LeafSnap, Flora Incognita, PlanNet are the most usable plant
identifiers apps.
3. It was shown that Flora Incognita correctly identified plant species in 71% case and
PlantNet correctly does this in 55 % case which is significantly lesser than the same
parameter for Google Lens (92.6 %). Google Lens was characterized by the highest
mark of usability compare to PlantNet and Flora Incognita.
4. Therefore, Google Lens is the most recommended app to use during biology classes.
However, for those students and teachers who do not like the Google Lens app, it is
possible to use Flora Incognita.
5. PlantNet app, which is characterized by an accuracy of 55 % can’t be recommended
to use during biology classes at all.
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