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    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Improvement of Agricultural Productivity with the Use of Advanced ICT Tools</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Dionysis Bochtis</string-name>
          <email>dbochtis@ireteth.certh.gr</email>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Charisios Achillas</string-name>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Dimitrios Aidonis</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Stelios Tamvakidis</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Giorgos Vasileiadis</string-name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Decentralized Administration of Macedonia-Thrace</institution>
          ,
          <addr-line>Navarinou 28, 55131 Thessaloniki</addr-line>
          ,
          <country country="GR">Greece</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Department of Logistics, Technological Educational Institute of Central Macedonia, Branch of Katerini</institution>
          ,
          <addr-line>60100 Katerini</addr-line>
          ,
          <country country="GR">Greece</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Engineers for Business (EfB)</institution>
          ,
          <addr-line>Doiranis 17, 54639 Thessaloniki</addr-line>
          ,
          <country country="GR">Greece</country>
        </aff>
        <aff id="aff3">
          <label>3</label>
          <institution>Institute for Bio-economy and Agri-technology (IBO), Centre for Research &amp; Technology - Hellas (CERTH)</institution>
          ,
          <addr-line>6th km Charilaou-Thermi Rd, GR 57001 Thermi, Thessaloniki</addr-line>
          ,
          <country country="GR">Greece</country>
        </aff>
      </contrib-group>
      <fpage>243</fpage>
      <lpage>249</lpage>
      <abstract>
        <p>Food consumption continuously increases in global scale over the years. To satisfy the growing demand for food production, farmers need to increase productivity. This can be achieved either with the use of larger and more productive and efficient agricultural machinery or with improved management and organization of the agricultural production. The former is now impeded due to environmental and biological factors. The utilization of large and more productive machines in agriculture has limited capabilities to further improve machinery productivity and efficiency, since the size and weight of the machinery is constrained by soil compaction, and further improvements to effectiveness are not available. However, the late advances in Information Technologies provide excellent opportunities for substantial improvements in the efficiency of advanced machines. In this work, an agricultural fleet management product, namely V-Agrifleet, is presented.</p>
      </abstract>
      <kwd-group>
        <kwd>Operations management</kwd>
        <kwd>decision-making</kwd>
        <kwd>real time planning</kwd>
        <kwd>voice-driven</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1 Introduction</title>
      <p>
        During the last decades, agricultural production has to deal with increased demands
for agricultural products. For increased production, there is large potential for
optimizing the interaction between individual machines, for multiple-machine
cooperation
        <xref ref-type="bibr" rid="ref1">(Bochtis et al., 2014)</xref>
        . Logistics management in the agri-food industries
involves transporting goods and services to local, regional and international
consumers. Agri-Fleet management and relevant industries require a high level of
coordination and cooperation to marshal resources more effectively
        <xref ref-type="bibr" rid="ref2 ref2 ref3 ref3">(Bochtis and
Sørensen, 2010; Sørensen and Bochtis, 2010)</xref>
        . Crucial challenges identified by all
industry stakeholders are; fleet cost-reduction, fuel price volatility, reduction of
accidents, increase of fleet and driver safety, intensification of agri-fleet productivity.
      </p>
      <p>In this light, a formalized management tool is needed, to support the management
of field operations. The complexity of agricultural field operation process and the
management activities contain logistical, economic and social links that constitute a
holistic management system. The V-AgriFleet application addresses this challenge
and aims to deliver an innovative agricultural fleet management system, in the form
of a mobile application, with central functional features of voice-driven information
provision and extraction, automatic recognition of machine operational modes, and
support real-time decision making. The application operates in heterogeneous fleets,
overcoming the drawbacks of the existing fleet management solutions which are
applicable solely for homogeneous fleets in terms of the vehicles/machines brand
names (i.e. “vendor locked”) and centre-focused (providing information only to the
central decision-maker). Moreover, through its voice-driven operations, the
application disengages operators from manual interaction with the system by giving
them the ability to interact with the mobile application (both for providing or
requesting information) by their own voice.</p>
      <p>The V-AgriFleet application constitutes a prototype (TRL6) that was developed
during the EU FP7 FRACTALS - Future Internet Enabled Agricultural Application /
FI-WARE (http://fractals-fp7.com) funded project “Voice-driven fleet management
system for agricultural operations” (Sub-Grant Agreement: 200-4594/18.05.2015).
2</p>
    </sec>
    <sec id="sec-2">
      <title>The Application</title>
      <p>Fleet Management Systems have long been available in the industrial domain, and
have evolved into complete enterprise management tools. In agriculture, more
advanced machinery as well as information technologies are being implemented,
enabling the implementation of the analogous fleet management tools. So far,
traditional industrial service offerings were mainly designed to service a single
machinery or a homogenous fleet of machineries (based on type or vendor etc.).
However, the low user acceptance due to the high cost of these systems, centralized
management orientation, and the required effort to receive and provide real time
information, inhibits integration of current fleet management systems into
agriculture. The current fleet management services are meant to service a finite set of
homogeneous and heterogeneous machineries (over different, locations, regions,
etc.).</p>
      <p>Various agricultural fleet management systems provide planning features (e.g.
route planning). However, the decision-making is addressed by the user. Automated
dynamic planning is an anticipated evolution in agricultural fleet management
systems corresponding to the variability of the parameters of the operational
environment in biological systems (e.g. yield variability, soil workability,
trafficability. etc.). The developed approaches lack an automated performance
evaluation process. The detection of operating modes for agricultural machines is a
future research topic for the agricultural fleet management domain.</p>
      <p>The following list presents an up-to-date perspective of the available approaches
to address the industrial challenges faced by the agri-fleet management industry: (a)
Planning approaches, such as vehicle routing, job-shop scheduling, floor shop
scheduling, and optimization approaches beyond the typical linear programming used
in the past (e.g., binary and integer programming) and entire system analysis
methodologies (such as Petri nets) are increasingly employed for formulating and
solving agricultural machinery planning processes; (b) the latest developments in
agricultural management provide the framework for planning operations executed by
co-operating multiple-machinery systems are a stepping stone for future fully
autonomous systems; (c) real-time decision support systems must be further
developed to close the loop of sensing-data interpreting decision making-actuating in
real-time machine control (e.g., in controlling inputs); (d) a lack of integration exists
between the different management levels, which prevents the full exploitation of the
precision and accuracy of the developed approaches and prevents their adaptation to
location-specific conditions.</p>
      <p>Present agricultural fleet management market is extremely fragmentary (the
majority of products are not compatible with different machinery vendors) and
current solutions available in the market have a number of disadvantages, such as: (a)
a centralized architecture providing all relevant information to a central decision
maker without providing any local machine-to-machine information exchange, (b)
information regarding the operational status of a machine (e.g. completion of a task)
is not automatically generated and requires manual interaction that requires time and
concentration, (c) the systems that are already available in the market require either a
homogenous fleet in terms of machines’ vendor or a system compatible with the
CAN bus of the machines.</p>
      <sec id="sec-2-1">
        <title>2.1 Design and Development</title>
        <p>In order to identify and map the environment of the application, a systematic
approach was implemented to guide the process, as seen in Fig. 1, through the
various steps of development. User/Stakeholder identification led to interviews that
aimed to deduce user needs in each aspect of use. To reduce the risk of bias and
misinterpretation, lists of user requirements were used, as seen in the work of
Sørensen and Bochtis (2010), adopted to the particular project. Through this process
various stakeholders contributed to forming a unique set of needs, that fully defines a
fleet management solution. Machinery contractors for example focused on transport
control, route guidance and data acquisition. Supplementary to this operational
outlook, more field related functionalities were requested by operators. Route
guidance, online monitoring and operations scheduling among others were their input
to the list of desired features. Requirements converged to core functionalities as
realtime positioning and tracking features, that V-AgriFleet needs to address efficiently.
Fig 1. Product development process
Fig 2. V-AgriFleet component architecture</p>
        <p>
          The quality function deployment (QFD) methodology was used to interpret these
requirements. QFD aims to translate user requirements to technical requirements
usable by the product developers and to guarantee that these are part of each step of
development
          <xref ref-type="bibr" rid="ref4 ref5">(Chan and Wu 2002; Khoo and Ho 1996)</xref>
          . This approach has the
potential to cover a wide area of the solution space and at the same time provide user
specified functionalities that ensure a high user satisfaction. Through this stepped
process following targets were reached:
i. Customer identification
ii. Customer requirements identification
iii. Customer requirements prioritization
iv. Design parameters identification
v. Relationship determination
vi. Design parameters correlation
Based on the processed inputs and the respective outputs of the process the
architecture of the application was designed to a three-tier form that meets all
technical and user requirements and simultaneously introduces an innovative
decentralized and peer to peer communication model. The outline of the application
architecture can be seen in Fig. 2.
        </p>
        <p>Furthermore, having identified the individual users involved and their respective
needs, the application was designed to provide a modular interface to the users. Each
user group has a customized interface and in case of multiple role users, these
interfaces can be combined. This safeguards the applications effectiveness, as its
offering of functions is optimized for each user, leaving an uncluttered clean
interface. This is crucial to field operations, when manual interactions are needed to
extract or to input data to the system and any delay or lack of focus can be costly or
dangerous. Examples of these individualized interfaces are shown in Fig. 3.
Fig 3. V-AgriFleet interface screenshots</p>
        <p>The V-AgriFleet solution addresses and tackles the current industry challenges
and replies to current market needs, delivering a product/solution in line with current
trends, inclusive of innovative technology and offers greater interoperability
compared with systems that are currently available on the market. V-AgriFleet
application, through the convergence of the decentralized fleet management and
context aware fleet operation, is expected to speed up the take-up from potential
clients that will employ this innovative process and underpin them as the future’s
businesses and at the same time, application is independent of the CAN bus use and
can serve any combination of homogeneous or heterogeneous fleets.</p>
      </sec>
      <sec id="sec-2-2">
        <title>2.2 Outcomes and Benefits</title>
        <p>An obvious and expected result is the fuel savings, resulting from optimized routes in
field operations as well as in travelling between fields, depositories, full loads etc.
This is a twofold profit as economical fuel management means by definition reduced
CO2 emissions and therefore a step closer to a more sustainable operation. Other
resources as water and fertilizer are also used more efficiently as the constant
feedback of information combined by the decentralized decision process allows the
optimization of resource utilization. This optimization is also diffused in other facets
of the agricultural operational management, as in the workforce engagement, both in
terms of working hours but also in terms of quality as the enhanced role of operators
redefines their significance in the system. This means increased speeds and reduced
errors, thus higher yields and less out of specifications crop products. The majority of
these benefits reflect on an economic level to the industry but also define a new
standard of environmental protection along with influencing social and demographic
variables of the human forces involved. An indicative summary is presented in Fig.
4.</p>
        <p>Fig 4. Expected benefits and outcomes of V-AgriFleet utilization
3</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>Conclusions</title>
      <p>The V-AgriFleet application is expected to offer exponentially expanding
opportunities to its users. As a smart, decentralized, connected product, the
application brings to the market new innovative functionalities, far greater equipment
utilization and reliability, and cross-cutting capabilities that may transcend traditional
product boundaries. With the use of the application, decision making process within
agri-business is decentralized, driving entrepreneurship to re-think, re-evaluate and
re-tool their day-to-day operations, making ICT become an integral part of the
agricultural production. Apart from the economic benefits, the optimized fleet
scheduling will result into reduction of the emissions and thus improved
environmental performance of the fleet.</p>
    </sec>
  </body>
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