Challenges in implementation of automated identification technology.
Stankovski, S. ; Ostojic, G.
1. Introduction
Every company needs consistent data about their
manufacturing/service operation, in order to wholly exploit
production/service capacity. Automated identification technology (AIT)
enables accurate data collection and it can be used in a wide range of
applications. The applications vary from process automation (tracking
products and assets/supply chain), heAITh care systems, to access
control (Turcua et al., 2013, Karkkainen et al., 2003, Karakostas,
2013). AIT relies on connection of a variety of identification devices
in computer integrated system. These devices, such as bar codes,
magnetic strips, smart cards, optical memory cards, RFID (Radio
Frequency IDentification) tags (Lahiri, 2007), NFC (Near Field
Communication) tags or/and biometrics (face, fingerprint, signature,
voice, iris, retina, and DNA (Deoxyribonucleic Acid)) identification
marks use for marking or tagging individual items, multi-packs,
equipment, air pallets, containers, etc. All devices are equipped with
the hardware and software required to read the information on them, and
integrate that information with other information in computer integrated
system. When AIT is properly implemented into a business, costs can be
reduced and the business will become more competitive.
Nowadays, devices which are used in applications with AIT have
enough power processor with unique number (called an IP (Internet
Protocol) address) to be a part of network of computers. This capability
is used to connect these devices in a network call Internet of Things
(IoT) (Gubbi et al., 2013). IoT sometimes referred to as the Internet of
Objects, will change a lot of things. The vision of IoT is to attach
tiny devices to every single object to make it identifiable by its own
unique IP address. These devices can then autonomously communicate with
one another and any others processor in the network. It is out of
question to ask how many challenges is open now. One of them is recently
launched "Cloud of Things" initiative joins several ongoing
projects at the Auto-ID Labs on MIT (Massachusetts Institute of
Technology), to connect physical objects such as vehicles and buildings
to the cloud. The "Cloud of Things" builds on the IoT, where
information about objects is accessed via the Internet; and
machine-to-machine (M2M) computing, where wireless communication
protocols enable peer-to-peer exchange of data between electronic
devices (http://web.mit.edu/newsoffice/2012/auto-id-cloud-of-things-bigdata.html). Similar projects based on AIT can be found at almost every
university in the world.
Since 2005 year, Automated Identification Technology (AIT) is
intensive researched at Department of Industrial Engineering and
Management (DIEM), Faculty of Technical Sciences, University of Novi
Sad. Main financial support is obtained through grants which are
financed by the Ministry for Science and the Provincial Secretariat for
Science and Technological Development. The grants: The implementation of
RFID (Radio Frequency IDentification), RFID technology in the supply
chain, Automated systems for identification and tracking of objects in
industrial and non-industrial systems, are enabled research is several
fields, like: manufacturing production, supply chain, access control,
agricultural business, vending machines, payment, etc. The focus of this
research is given to the use of RFID technology as the core technology
for identification in most applications. Ones again, it is important to
be noted that the successful implementation of the AIT depends on
successfully connecting to the rest of an information system. In the
text below will be will present the results achieved in the
implementation of the AIT on the Department of Industrial Engineering.
The first will be described in the general part about the RFID
technology (Stankovski et al., 2009a, Stankovski et al., 2012). After
this chapter, it will be present the results obtained in the fields of
Product lifecycle management (Stankovski et al., 2010), and Agricultural
business (Stankovski et al., 2012).
2. RFID Technology
RFID is a system for automated data acquisition which allows
collection and wireless (radio wave) transfer of production- and
business-related data. RFID technology is suitable for usage on plastic
product/parts (Inkenzeller, 2003.). Since the moment, a product is
manufactured, to the beginning of its exploitation or disassembly, RFID
technology allows real-time identification, during delivery, storage, or
any other process taking place within an enterprise. By means of radio
waves, the data are acquisitioned and transferred in wireless mode
between production and business processes in real time. This unique way
of identification is adjusted in such a way that it allows the
information on product to correspond to the information on the side of
the company or the host system. Using RFID technology, it is possible to
track products and equipment, with minimum human intervention. This can
potentially cut back operating costs and increase real-time visibility
during complete product life cycle.
RFID system consists of: a computer (or Programmable Logic
Controller (PLC)), RFID reader, antenna (which can be integrated in a
RFID reader) and transponder--tag (Fig. 1). The antenna is used to
amplify the signal, which is emitted by the reader to the tag, as well
as the signal, which is returned to the reader by the tag, which
increases the tag-reading range. RFID reader can be a stationary or a
portable device, which can activate and pick up the signals emitted by
the tags. It consists of the power unit, antenna and a printed circuit
board, and its primary role is to receive and send RF (Radio Frequency)
signals to the tags by means of antenna. From a computer or a PLC, the
reader receives instructions generated by the dedicated software. The
control unit inside the reader executes the received instructions
(Inkenzeller, 2003; Glover & Bhatt, 2006).
The readers differ by the range and operating frequency. Similar to
the tags, the readers can have small range (up to several centimetres),
medium range (up to 1 meter), and long range (tens of meters, with an
additional antenna).
[FIGURE 1 OMITTED]
The tags consist of a microchip (which stores alpha-numerical code
for product labelling), an antenna (copper wire--coil) and an optional
power source (e.g. battery). They exist in a variety of forms: various
pendants, circular or square plates, magnetic cards, or some other form,
depending on the area of application (Fig. 2). Smart labels are a
special type of tags which can be placed on, or built into a palette or
any sort of product.
[FIGURE 2 OMITTED]
The components of RFID systems are selected depending on the area
of application. Of primary consequence is the operating frequency of the
components (Fig. 3). In most of the countries, the operating frequencies
for RFID systems are strictly defined.
Once RFID tag enters reader's operating range, the reader
detects its activation signal. The reader then decodes the data coded in
tag's integrated circuit and the data is transferred to the
computer for processing. Significant advantage of RFID systems is that
they do not require contact for proper functioning. Tags can be read in
any industrial environment, which can involve snow, fog, ice, color
stains, dirt and similar. RFID tags also read fast--in most cases the
response is faster than 100 milliseconds. New generation of readers have
ability to simultaneously read several tags. Thus whole storage area can
be read at once instead of scanning each article individually (Shepard,
2005).
[FIGURE 3 OMITTED]
3. AIT in Product Lifecycle Management
All phases of the product life cycle, starting from the first
phase--production, following with distribution, sales, usage, service
and maintenance to the phases coming at the end of the life cycle
(disassembly, recycling, reassembly, incineration, waste disposal) is
presented in Fig 4. It is important to emphasize that not every, but
most of the products pass through the mentioned phases during their life
cycle.
Disassembly is just one of the processes in the life cycle of a
product and lately it has attracted a lot of attention, considering its
key role in reassembling and recycling of products. This is due to
ecological and economical reasons. The ecological side of the problem is
seen in ending numerous products at waste dumps and in depletion of
non-renewable natural riches. The economical side of the problem of
disassembly is seen in the need for a design of the disassembly system
in a way that the value of the disassembly process result is grater then
the resources invested for its proper functioning (Lazarevic, 2009).
When designing disassembly system the designer has to consider end of
life strategies and strategies selection for product.
[FIGURE 4 OMITTED]
Users of products have two crucial difficult decisions to make: one
is decision when to replace a product after its use and the other is
what to do with the products when they decide to replace it. It is not
unusual for some users to decide to sell the product and replace it
while it is still in good condition. Therefore, the price of that kind
of product is higher and the budget for buying a new, technologically
advanced product is also higher. There are also some users which utilize
their products until they became technologically outdated. After that,
they leave them to the company responsible for end of life product
processing. For many different reasons products arrive to the end of
life product storage. Some of them may be discarded, but their vital
elements can be in good condition, so they can be reused as spare parts
in the maintenance process. All this leads to a conclusion that there is
a need to determine strategies for the product at the end of life cycle.
Studies related with the strategies of the products end of a life
cycle are numerous (Lazarevic, 2009; Mehl et al., 1994). The most
accepted, and in its character, the most comprehensive classification of
the products end of a life cycle is (Rose et al., 1999):
1) re-use of used products,
2) reconstruction of used products,
3) usage of already used products for spare parts,
4) recycling with disassembly,
5) recycling without disassembly,
6) dumping of the used products.
Re-use of already used products is a strategy that organizes the
return of discarded products which are still in function. If such an
interest exists, already used products are sold in the market.
Reconstruction of used products is applied due to modernize or to
upgrade their performances. The purpose of this strategy is to attain a
product, which is in quality less or very similar to the quality of the
new products. The quality of the reconstructed products depends on the
determined depth of disassembly. If a product is disassembled to the
level of parts and a control and a replacement of all parts is
conducted, the used products are brought to a high level of quality,
required for the new products. Also, it is possible to conduct the
modernization of products, by replacing certain modules with
contemporary ones, after applying the disassembly. Appliance of already
exploited products for spare parts is being frequently used. In certain
companies, out of date products are being collected in an organized
manner. The purpose of this strategy is to take a relatively small part
of sub modules from a used product and use them for the above mentioned
strategy, or for another purpose, and the rest will be used for material
recycling. Recycling with disassembly is a strategy used for separating
parts made of different material, before its conversion in the process
of disassembly. The purpose of this strategy is to use
the materials from the used products and parts, by separating them in
the procedure of disassembly into the element parts and with appropriate
selection, depending on the determined type of material. These materials
can then be used in the production of original or some other products.
Recycling without disassembly is a procedure, which is used to compact
and compress the product and then crush it and sort it by type of
material. Disposal is, from the ecological point of view, the most
inconvenient strategy for disposing products on the waste dumps. Having
the above mentioned strategies in mind, it is necessary to design an
appropriate production system. The system for product processing at the
end of life cycle has a quite complex structure, since there is a need
for more then one technologically different subsystem like (Lazarevic,
2009):
1. disassembly,
2. reassembly,
3. recycling,
4. waste incineration,
5. hazardous waste storage,
6. waste storage.
The choice of strategies for reconstruction of used products (2),
usage of already used products for spare parts (3) and recycling with
disassembly (4) are made according with the both momentary product
condition and suggestions taken from the database for particular
product. A system for product processing, according with chosen
strategies for product management at the end of the life cycle, is shown
in the next figure (Lazarevic, 2009).
[FIGURE 5 OMITTED]
In the most general case, if for the given product (pi), all three
potential strategies are chosen as possible, which comprise the need for
disassembly (strategies 2, 3 and 4), then the production system for
processing of such products contains in itself all the elements as in
the previous figure. In case when only the strategy number 4 is chosen,
then a subsystem for repair does not exist.
When choosing strategies 3 and 4, a subsystem for repair possibly
exists. Depending on the type of product and the type of repair, the
repair subsystem does not have to be specially separated. It is
important to notice that in the procedure of the product disassembly,
during the parts selection, a flow of materials must be planed for the
parts that are headed for reassembly. In other words, it is often very
possible to conduct, in a same place, within one subsystem where the
disassembly is conducted, a second assembly of the product. In order to
ensure the adequate supervision and control in all the phases of the
product life cycle (depending on the type of product and level of
supervision and control), an appropriate automated system is designed.
Hardware system elements depend of the function to be executed in
specific phases of the product life cycle, but the basic component is
only a PC with Intranet/Internet connection and any kind of Internet
browser. This kind of system enables only supervision in some of the
phases where this supervision function should be available. This basic
system can be expanded by adding a RFID reader and its connection to PC
(RS 232, USB, or TCP/IP), but only in some of the phases of the product
life cycle, where the control function is needed. The software system
components include web-based application software, and the software
application depends directly on selected products end-of-life strategy
defined in the product design phase.
As presented in Fig. 4. and 5., the automated system for product
monitoring enables interactive communication between the database, user
and product in every phase of the product life cycle. The system
designed in this way enables authorized
[FIGURE 6 OMITTED]
In some phases, during the product life cycle, it is necessary to
change information about the product. This activity is done by
authorized users responsible for writing this information, whether only
to the database or both to the database and RFID tag placed on the
product, thus enabling updating information about the current status of
the product. Information placed in the database about a product
includes:
* Product ID (UID read from the RFID tag assigned to a particular
product).
* Product type.
* Date of issue.
* Date of first start.
* Recommended strategy for product.
* Recommended level of disassembly depending on the chosen strategy
for the product.
* What elements can be used for spare parts?
* Services (dates and descriptions).
* Number of working cycles.
* Does it contain hazardous parts and materials?
* Does it contain already used parts or recycled materials? If so,
which parts are those and what is the number of the remaining working
cycles?
* Which part is the base part for assembly? etc.
Since assembly and disassembly phases of product life cycle are one
of the most important special attention has been given to the structure
of these systems. An example of RFID technology application is shown in
Fig. 7. The proposed concept can be used for assembly and disassembly of
product in order to increase flexibility and efficiency rate of the
system in hand. Products can be assembled and disassembled on the same
technological system according to the process plan and the product
currently available at a particular working place.
An example of assembly is given in Fig. 7 and it follows the next
routine: conveyer belt brings in the parts tagged with RFID. Upon
arrival of the part at the first working place, the reader reads the
RFID tag. The read out UID is compared to the UID from the data base,
after which the data base issues a number of instructions for assembly
presented graphically on-screen to the operator. The instructions are
presented in a sequential manner, and are executed by taking the
appropriate tool. Upon return of the tool to its previous position, next
assembly instruction is initiated.
[FIGURE 7 OMITTED]
If a sequence requires no tool, then the next instruction must be
initiated manually. Upon completion of the operation (all sequence of
operation), the sequence of instruction for that particular working
place is finished. The product is placed on the conveyor belt, travels
along and, gets identified by RFID once again on another working place.
If the product is to be machined at that particular working place, the
signal light flashes and the operator takes the product off the conveyor
belt. The process continues like in previous operation with a number of
instructions coded for that working place and that product. In case all
working places are currently busy, the product circles on the conveyor
belt until a vacancy appears. The RFID tag is always placed on the base
part.
4. AIT in Agricultural Business
The identification of cattle on the territory of the Republic of
Serbia is obligatory. It is performed within 20 days after birth or
before leaving the birth farm, by double ear labels on both ears fixed
through the auricle. The ear labels have a unified code for the
identification of each calf individually. This code is in a form of
barcode with the structure represented in Fig. 8. The first two letters
represent the country code, while the ten-digit number represents the
unique number assigned to the particular animal. The first digit is the
country code (7--Serbia), the second digit is the cattle breed code
(1--cow), the third digit is a control digit assigned by the central
base, and the remaining 7 digits are the animal identifier.
[FIGURE 8 OMITTED]
In the research that has been carried out on farms, barcode
identification has proved inefficient for many reasons, e.g.:
* To identify the animal, as barcode reading is possible only on
short distances, one must physically approach the animal, which disturbs
it.
* The farm worker must spend his working time in data reading,
which directly influences the farm's productivity and expenses.
* Errors occur during the manual data input to the PC.
* As the animals are in a dirty environment, mud and other dirt are
often found on the ear labels, which complicate the identification of
the animal, as more reading attempts are required.
* Recording changes about the individual animal data is not
possible locally, as barcode possesses no memory where the data can be
stored, instead it is necessary to modify the data in a unified
database, which can be inaccessible for different reasons (no adequate
infrastructure, etc.), and also requires additional involvement of the
user.
* Barcode dedicated to an animal can be used only once, as no
modification of data is possible.
* Barcode can easily be duplicated, which opens the possibilities
for abuse.
Taking into account the fact that the identification of cattle
(dairy cows) is obligatory, and that it is being performed in the above
described manner, as well as the problems noticed on the farms, the idea
came up to use RFID technology for identification and milking cycle
tracking for each calf (dairy cow), due to the importance of regular
milking cycles. This is one of the key influencing parameters for
achieving a better and higher quality milk yield. Monitoring of the
milking cycles can bring benefit to the following:
* By monitoring the entering sequence of cows to the milking
facility, milk quality can be influenced (it is possible to monitor
whether heAIThy animals come first, or the animals with suspicion of
disease, or if the ill animals or animals under therapy come to the
milking facility, whether the younger or the elder animals come first,
etc).
* With reports on the milking cycle, animal management can be
optimized by arranging the sequence of bringing the animals to the
milking facility and avoiding their crowding at the entrance. This can
reduce stress and agonistic interactions between the cows while they
wait to enter the milking facility, which leads to better overall
welfare of the cows, reduces the risk of hurting between the animals,
etc.
* If the animal is being fed with concentrated meals, then by the
report of the time spent in the milking facility and its production, the
amount of food for the animal can be optimized.
An RFID-based dairy cow monitoring system has been implemented on a
dairy farm with three hundred and five of all categories
Holstein-Frisian breed in the municipality Vrbas in the Republic of
Serbia, in February 2009, and it has been used until May 2009 for the
purpose of this experiment. After that period it has been used in
regular operation. This system is used not only for the identification
of each calf, but also for monitoring the entire milking cycle. Milking
system was herringbone and each cow was admitted through an entrance
gate. The cows were washed under the sprinkler systems and each cow
entered an individual box. This system not only provided safe and
correct cow positioning, but there was also good visibility of the
animal's udder to the milker. Also, it is important to mention that
the cows were provided with feed concentrate, and the milker wiped the
udder with cloth and put on the milking cluster. All cows were milked
twice daily and the samplings were taken for each cow outcome by milk
meters (Metatron 12), according to ICAR (International Committee for
Animal Recording) rules. On the farm milk samples are collected ones in
four weeks, but for experiment milk samples were collected each day and
carried in the laboratory of the Agricultural Faculty in Novi Sad. These
samples were representing the 24 hour milking period. Analyzes of the
chemical components of milk samples (milk fat (MF), protein (P), lactose
(L), dry matter (DM)) are done with routine methods. Also, the total
bacteriological count (TBC) is obtained by method--flow cytometry using
Bacto-Scan (Foss Analytical equipment).
Statistical analyses (average values, standard deviation and
t-test) were carried out through software Statistica 9.1 (from StatSoft,
Inc.).
The advanced RFID system is implemented in the milking facility.
The RFID system comprises the following major hardware components:
1. Control box, containing a computer connected to a system of
uninterruptible power supply,
2. Two UHF RFID readers operating at frequency of 915 MHz ((Fig. 9
a) and Fig. 9 b)), and
3. Two hundred and ten RFID tags glued onto the dairy cow ear
labels (Fig. 10).
The UHF RFID readers are placed at the entrance and the exit of the
milking facility above the door so that they do not hinder in any way
the entry/exit of dairy cows, nor the workers carrying out tasks in the
facility. The maximum length at which a reliable UHF RFID tag data
reading can be performed is 10 m.
[FIGURE 9 OMITTED]
Since the UHF RFID technology allows longer distances for tag
recognition (even up to 10 meters), the installation of RFID readers in
the existing facilities is easier and does not affect to a larger extent
the already established movement of cows within the room where the
identification is being conducted (in this particular case: the milking
facility).
[FIGURE 10 OMITTED]
The computer in the control box is primarily used for data
acquisition from the RFID tags placed onto the ear labels and archive
data on the hard disc of the computer. The following software components
are installed on the computer:
1. An application which communicates with the RFID readers, and
collects data from the RFID tags (UID--Unique Identifier, a single
number for each card).
2. An application for the analysis of the data collected from the
RFID tags for the purpose of identifying the milk cycle of each dairy
cow.
These two applications enable monitoring, data acquisition, archive
and analysis of a milk cycle of each dairy cow.
The experimental period at the farm lasted for 85 days. The owners
of the small cattle farm could follow every step of the field trials,
being able to understand the procedure. The results collected on the
small cattle farm enabled the determination of behavioral patterns, i.e.
it was possible to determine the order in which the cows were coming to
the milking facility. Changes in this order were happening
stochastically, which influenced the milk quality and yield of each
dairy cow. Cows having a settled milking cycle within an interval of 12h
[+ or -] 5% (group 1) had a 1.5% better daily milk yield and a 0.08
better quality in comparison to cows with a milking cycle variance
higher than 20% (group 2). Average value [+ or -] standard deviations of
daily milk yield and milk quality are shown in Tab. 1.
Low values of daily milk yield in group with a milking cycle
variance higher than 20% (group 2) are in according with other authors
(Davis et al., 1999; Hale et al., 2003; Hassabo, 2009; Tagelsir, 1991).
Circulatory and nervous system play an important role in milk synthesis,
secretion and let down which is affected by neurohormonal effect and
synchronization (Tagelsir, 1991). Becouse of that once a day milking or
skipping milking is not acceptable with high producing dairy cows under
intensified dairy system, while twice a day milking interval of 10-14 h
and 12-14 h are acceptable, while 3 times a day milking will increase
milk up to 12-15%. Furthermore, four times a day milking will increase
milk production from 8-12% over, (Hassabo, 2009). Once-daily milking
(ODM) of ruminants results in loss of milk production. In cows this loss
is very variable between individuals but in recent short-term trials, on
average, the loss was 13% (Davis et al., 1999). Milking frequency can be
increased in a manner that minimizes additional labour by employing
unequal milking intervals (Hale et al. 2003). Total bacteriological
count was in according with 39% the best samples of Casoli et al.
(2010). During the experimental period, no serious problems were
detected. Animals responded well to tag application and no effect on the
animals' welfare was observed. Moreover, the animal's heAITh
status was not affected by the devices because the UHF RFID tags were
glued onto the dairy cow ear labels (Fig. 10). The only problem that was
observed was related to the RFID reading accuracy. In the Tab. 2 the
results of the RFID reading accuracy are presented. In order to remove
faults due to the reading accuracy of the RFID reader or loss of ear
tags, four additional ultrasonic sensors and four limit switches were
placed. Each cow is located in a separate box and before the milking
starts, the box must be closed, which is guaranteed by the signal from
the matching limit switch. After that, the presence of cow in the box is
determined and the cows are enumerated by using the ultrasonic sensors.
At the end of the milking cycle, the data about the enumerated cows
from the RFID system and from the sensor system are compared. In case
that these numbers do not match, the system generates a list of cows
that were not identified by using the RFID system.
During the first week of the experiment, the problem with the RFID
reading accuracy was observed, and the necessary adjustments of the RFID
readers were performed. After this period, the variations of the RFID
reading accuracy were settled. For these reasons the results were
represented in the form given in Tab. 2. The results acquired within the
research led to the idea of designing a system that would generate a
decision on the optimal path for each animal to the milking facility or
the redirection to the waiting facility based on the established milking
cycle for each animal and the determination of the actual situation at
the entrance (identification of the animal currently at the entrance).
It is important to emphasize that the animal identification process with
the use of UHF RFID technology is such that at the time of
identification the animal is not aware of the procedure, so the
procedure does not cause stress, which would also have negative
influence on the yield and quality of milk. This is not the case with
the other identification methods, such as the manual or the automatic
method which uses bar codes. Another advantage of the implemented system
is that it can work autonomously, and, if required, it can be easily
integrated into the new or existing complex farm management systems.
5. Conclusion & Future Challenges
Automated identification technology is one of the most promising
technologies in the future. Small and cheap electronic elements are
enabled development of the identification devices with big processing
power. These characteristics with communication are crucial to
connection with wide range of devices, such as: computers, controllers,
phones, etc. With these opportunities automated identification
technology can be used in nearly every business in the world. In this
moment, AIT is primarily used in applications such as tracking products
and assets/supply chain, access control, heAITh care systems, payments,
etc.
Certainly, as one of the biggest challenges in the future will be
monitoring and traceability of a food with the use of smart phones. This
conclusion is coming from the fact that the food product traceability is
a topic a lot of papers in main world journals. In order to set a
traceability system, it is necessary to provide updated data that is
significant to the user, such as the product origin, processing mode,
storing conditions, expiration date etc. In each system there is a
critical point where the systematic information loss occurs when the
information about a product or process is not linked to a product and
recorded systematically (Hu et al., 2013), thus it is important to set
the system so that the potential critical points are recognized and the
problems eliminated before the implementation of the traceability
system.
The appearance of the avian and swine influenza, bovine spongiform
encephalopathy ("the mad cow disease") as well as frequent
occurrence of undesirable substances (pesticides, heavy metals, etc.) in
food products increases the need for an efficient system for tracing the
origin and the processing conditions of food during production,
transport and warehousing. Product traceability is an efficient way for
increasing food safety and quality and to reduce the expenses for
withdrawal of problematic products from the market (Regattieri et al.,
2007), as well as to improve production strategies in a company (Saltini
and Akkerman, 2012) and production controll (SAITini et al., 2013).
Product traceability is extremely important for perishable products
industry (Lavelli, 2013). The European Union countries, this area is
regulated with European standards for traceability and Best Available
Technology (BAT), as laid down in EN ISO 2205:2007 standards and the
European Directive 2008/1/EC (Standardization, 2007). On the other hand,
it is shown that the modern way of life leads to separation of users
(consumers) and producers of food products (farmers, agriculturalists)
from each other (Frewer et al., 2005; Harper and Makatouni, 2002; Maria,
2006; Phuong, 2013; Verbeke, 2005). This separation influences the
increase in consumers distrust in the food product quality, different
interpretations of conditions in which the animals should be held in
order to gain satisfactory quality of food products from a certain land
property (Bosona and Gebresenbet, 2013; Vanhonacker et al., 2008).
A study (Zhang et al., 2012) shows that the consumers are willing
to pay a significant positive price premium for food traceability, as
such a system greatly influences the consumers trust in a certain
product (Chen and Huang, 2013). (Cunha et al., 2010) shows a system for
vineyard identification and vine origin based on a QR code printed on
the container where the vine is transported. By reading the QR code by
the mobile phone and using the internet, a user can get information
about the origin, weather and other conditions in the field during the
growth of grapes. This project also used other technologies, like the
RFID tags, determining location by GPS, measurement of temperature,
humidity and air pollution. A similar concept of traceability is shown
in (Ruiz-Garcia et al., 2010), where data from the field are collected
through web-based systems for data processing. There are also studies
where product traceability is used in analysis of product quality at the
end of product lifecycle and the products are classified based on these
results (Papetti et al., 2012; Zhang et al., 2010). (Qian et al., 2012)
describe a study with a primary goal to develop a Wheat Flour Milling
Traceability System (WFMTS), incorporating 2D barcode and radio
frequency identification (RFID) technology, and to validate the system
in a wheat flour mill in Chinese. Tracing each individual product is
based on 64 applications of QR codes, and tracing a container with
several products is based on application of RFID tags. The system
described by this study is successfully implemented in a real world
application.
Application of 2D codes is also present at farms, and thus
(Froschle et al., 2009) presents results that indicate applicability of
Data Matrix codes for product traceability for each individual animal at
poultry farms. The codes are printed on the beak and feet of the animal,
and the reading of codes is performed by optical devices. It was shown
that the codes printed on the beak have better read rates than those
printed on the feet. Another similar research (Mclnerney et al., 2011a,
2011b) analyzed the influence of renewing the surface of the chicken
beak during the traceability period to the readability of linear and 2D
barcodes that were printed on the beak. It was shown that regardless of
the renewing of the beak cells, the codes are mostly readable.
In the analysis of the data (www.firstdata.com), it is discovered
that the biggest predictor of behaviour and attitudes is whether or not
the consumer uses a smart phone. (All smart phones can be used as the
part of AIT.) That differentiation is also driven by age, with
Millennials (ages 18-34) leading the way, but Millennials are also more
likely to own and use a smart phone. The analysis shows that nearly 100%
mobile phone penetration among survey respondents, that smart phone
penetration varies around the globe, with China (92%), Singapore (89%)
and the Middle East (80%) showing highest smart phone penetration. But
even in countries later on the smart phone adoption curve, approximately
one half already use a smart phone. In the United States, smart phone
penetration up to 68%, with large growth in the 55+ age group in the
past six months alone. This is very important, because the 55+ age group
usually pays more attention to the quality of food. As a global average,
80% of Millennials use a smart phone, and it's just a matter of
time before the majority of global consumers will be online anytime and
anywhere. (This is truly challenges, not only for AIT!) This opportunity
is crucial to success of all projects of monitoring and traceability of
the food.
In this chapter is presented several application based on RFID
technology (the core technology for identification in most applications)
developed at Department of Industrial Engineering and Management,
Faculty of Technical Sciences, University of Novi Sad. These
applications are results of research in the fields: product lifecycle
management, access control and agricultural business. Also, one of the
future researches challenges of AIT is discussed.
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Authors' data: Univ.Prof. Dipl.-Ing. Stankovski, S[tevan];
Assistant Prof. Dr. Sc. Ostojic, G[ordana], University of Novi Sad,
Faculty of Technical Sciences, Trg Dositeja Obradovica 6, 21000 Novi
Sad, Serbia, stevan@uns.ac.rs, goca@uns.ac.rs.
DOI: 10.2507/daaam. scibook.2013.02
Tab. 1. Average value [+ or -] standard deviation of milk yield
and milk quality and different between groups
Group MY (kg) MF %
1 27.1 [+ or -] 5.35 3.573 [+ or -] 0.558
2 26.7 [+ or -] 5.62 3.571 [+ or -] 0.700
P-value 0.0468 * 0.4499 (nz)
Group P % L %
1 3.201 [+ or -] 0.323 4.300 [+ or -] 0.346
2 3.198 [+ or -] 0.490 4.297 [+ or -] 0.269
P-value 0.5219 (nz) 0.5837 (nz)
Group DM % tbc
1 12.302 [+ or -] 0.743 42589 [+ or -] 8423
2 12.211 [+ or -] 1.182 42591 [+ or -] 9280
P-value 0.0934 (nz) 0.4499 (nz)
* Significant p < 0.05; NS- Not significant p > 0.05
Tab. 2. Results of the reading accuracy in the experimental
period
Reading accuracy during Minimum Maximum Average
experimental period per day per day per period
Period I (first week) 94.8% 98.6% 97.3%
Period II (the rest of 99.2% 100% 99.8%
the period)