<commit_before>
@online{_state_????,
  langid = {english},
  title = {The State of Automation in Horticulture},
  url = {http://www.greenhousemag.com/article/creating-smarter-systems/},
  abstract = {Vineland’s Dr. <NAME> discusses smart irrigation systems and more.},
  journaltitle = {Greenhouse Management},
  urldate = {2018-04-04},
  date = {2017-02},
  author = {<NAME>.},
  file = {/Users/tatu/Zotero/storage/5JUDFTTJ/creating-smarter-systems.html},
  note = {00000}
}

@book{gilchrist2016industry,
  title = {Industry 4.0: {{The Industrial Internet}} of {{Things}}},
  isbn = {978-1-4842-2047-4},
  url = {https://books.google.fi/books?id=YuOODAAAQBAJ},
  publisher = {{Apress}},
  date = {2016},
  author = {<NAME>.},
  note = {00066}
}

@book{buyya2016internet,
  title = {Internet of {{Things}}: {{Principles}} and {{Paradigms}}},
  isbn = {978-0-12-809347-4},
  url = {https://books.google.fi/books?id=_k11CwAAQBAJ},
  publisher = {{Elsevier Science}},
  date = {2016},
  author = {<NAME>. and <NAME>.},
  note = {00059}
}

@inproceedings{maSmartMeteorologicalService2017,
  title = {A Smart Meteorological Service Model Based on Big {{Data}}: {{A}} Value Creation Perspective},
  doi = {10.1109/GSIS.2017.8077722},
  shorttitle = {A Smart Meteorological Service Model Based on Big {{Data}}},
  abstract = {With the rapid development of cloud computing, the Internet of things, big data has become one of the hot spots of society, but also a major focus of applied research, made many service sectors to become data-driven organizations, which exploit the value of big data resources to gain competitive advantage. The meteorological department and the Internet online monitoring collected a large number of meteorological data, deeply develop meteorological data value by using big data analysis method, also by comparing the data and model analysis technology. Within this paper, a literature review, surveys and expert interviews were used in this research paradigm, it analyzed the meteorological observation data management service system, proposed a value-driven smart meteorological service model based on big data. The aim of this paper is to construct a value-driven smart meteorological big data service model that includes resource collaboration, technical collaboration, and service collaboration, optimize the meteorological forecast processes. This promotes meteorological related services products more fine, more accurate and longer forecast timeliness in meteorological disaster prevention and mitigation, public transportation, flood control and drought, agricultural production, transportation and other areas.},
  eventtitle = {2017 {{International Conference}} on {{Grey Systems}} and {{Intelligent Services}} ({{GSIS}})},
  booktitle = {2017 {{International Conference}} on {{Grey Systems}} and {{Intelligent Services}} ({{GSIS}})},
  date = {2017-08},
  pages = {299-305},
  keywords = {Big Data,big data analysis,cloud computing,data analysis,data management service system,data models,Data models,Economics,geophysics computing,Government,groupware,Industries,Internet of things,Internet online monitoring,meteorological data value,meteorological department,Meteorological Forecasting,meteorology,resource collaboration,service collaboration,Service Collaboration,Service Model,smart meteorological big data service model,technical collaboration,value creation,Weather forecasting,Web services},
  author = {<NAME>. and <NAME>.},
  file = {/Users/tatu/Zotero/storage/LFGUMWJ8/8077722.html},
  note = {00000}
}

@thesis{elovaaraAggregatingOPCUA2015,
  langid = {english},
  title = {Aggregating {{OPC UA Server}} for {{Remote Access}} to {{Agricultural Work Machines}}},
  url = {http://urn.fi/URN:NBN:fi:aalto-201509184356},
  abstract = {Agricultural machinery has improved rapidly during the last decades and the role of electronic controllers and sensors has increased. Simultaneously and partially because of this, the efficiency requirements concerning farming have grown more stringent. Information systems to help in farm management are already commonplace. Many work machines utilize the ISO 11783 communication protocol, through which a lot of data from the operation and internal state of a machine could be retrieved. However, this available data from agricultural work machines is not fully utilized. This thesis evaluates OPC UA aggregating servers as a centralized means to read and store the data available from multiple work machines.
 
 
This thesis builds on an earlier thesis where an OPC UA information model was developed for agricultural work machines utilizing the ISO 11783 communication protocol. First, a literature review was done to get a general view of the current state and the intended future of farm management systems, and to see how and where the data from the work machines can be utilized. Based on this and the previous work, the requirements for an aggregating server concentrating the information available from work machines running OPC UA servers were defined. A prototype aggregating server that is able to automatically transform the information from multiple ISO 11783 work machines to a unified view using a set of mapping rules was designed and implemented.
 
 
OPC UA aggregating servers were found to be viable technology for the centralized data monitoring and collection of ISO 11783 work machines. All relevant data exposed by the work machine OPC UA servers can also be accessed through the aggregating server. The mapping engine implemented on the aggregating server prototype can be extended to automatically map the information from other devices exposing themselves through OPC UA as well. The usefulness of an aggregating server increases if in the future OPC UA will be more commonly adopted and utilized by other agricultural equipment as well.},
  pagetotal = {68+7},
  institution = {{Aalto university}},
  urldate = {2018-04-23},
  date = {2015-08-24},
  author = {<NAME>},
  note = {00003}
}

@book{verdouwInternetThingsAgriculture2016a,
  title = {Internet of {{Things}} in Agriculture},
  volume = {11},
  abstract = {This literature review on Internet of Things (IoT) in agriculture and food, provides an overview of
existing applications, enabling technologies and main challenges ahead. The results of the review
show that this subject received attention by the scientific community from 2010 on and the number
of papers has increased since then. The literature on IoT in agriculture and food is very much
dominated by Asian scientists, especially from China. In other continents, the concept of IoT was up
to recently mainly adopted by non-agricultural scientists. The application area of food supply chains is
addressed most frequently, followed by arable farming. Most papers report the results of explorative
studies or they present IoT systems that are designed or implemented in prototypes and pilots. The
literature reviewed focuses on sensing and monitoring, while actuation and remote control is much
less addressed. The findings indicate that IoT is still in its infancy in the agriculture and food domain.
Applications are often fragmentary, lack seamless integration and especially more advanced solutions
are in an experimental stage of development. Important challenges to overcome this situation include
(i) integration of existing IoT solutions by open IoT architectures, platforms and standards,
(ii) upscaling the usage of interoperable IoT technologies beyond early adopters especially by the
simplification of existing solutions and make it more affordable for end users, and (iii) further
improvement of IoT technologies to ensure a broad usability in the diversity of the agri-food domain.},
  pagetotal = {1},
  date = {2016-12-01},
  author = {<NAME>},
  doi = {10.1079/PAVSNNR201611035},
  note = {00003}
}

@article{talaveraReviewIoTApplications2017,
  title = {Review of {{IoT}} Applications in Agro-Industrial and Environmental Fields},
  volume = {142},
  issn = {0168-1699},
  url = {http://www.sciencedirect.com/science/article/pii/S0168169917304155},
  doi = {10.1016/j.compag.2017.09.015},
  abstract = {This paper reviews agro-industrial and environmental applications that are using Internet of Things (IoT). It is motivated by the need to identify application areas, trends, architectures and open challenges in these two fields. The underlying survey was developed following a systematic literature review using academic documents written in English and published in peer-reviewed venues from 2006 to 2016. Selected references were clustered into four application domains corresponding to: monitoring, control, logistics, and prediction. Implementation-specific details from each selected reference were compiled to create usage distributions of sensors, actuators, power sources, edge computing modules, communication technologies, storage solutions, and visualization strategies. Finally, the results from the review were compiled into an IoT architecture that represents a wide range of current solutions in agro-industrial and environmental fields.},
  journaltitle = {Computers and Electronics in Agriculture},
  shortjournal = {Computers and Electronics in Agriculture},
  date = {2017-11-01},
  pages = {283-297},
  keywords = {Internet of things,IoT,Agro-industry,Environmental monitoring,Systematic literature review},
  author = {Talavera, <NAME> Tobón, <NAME> and Gómez, <NAME> and Culman, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>},
  note = {00002}
}

@book{vermesanInternetThingsGlobal2011,
  location = {{Aalborg, UNKNOWN}},
  title = {Internet of {{Things}} - {{Global Technological}} and {{Societal Trends}} from {{Smart Environments}} and {{Spaces}} to {{Green Ict}}},
  isbn = {978-87-92982-88-9},
  url = {http://ebookcentral.proquest.com/lib/haaga/detail.action?docID=3400141},
  publisher = {{River Publishers}},
  date = {2011},
  keywords = {Computer networks -- Europe.,Information technology -- Europe.,Internet -- Europe.,Internet research -- Europe.,Ubiquitous computing -- Europe.},
  author = {<NAME> and <NAME>},
  note = {00000}
}

<commit_msg>Interviev1 to bibliography<commit_after>
@online{_state_????,
  langid = {english},
  title = {The State of Automation in Horticulture},
  url = {http://www.greenhousemag.com/article/creating-smarter-systems/},
  abstract = {Vineland’s Dr. <NAME> discusses smart irrigation systems and more.},
  journaltitle = {Greenhouse Management},
  urldate = {2018-04-04},
  date = {2017-02},
  author = {Varga, <NAME>.},
  file = {/Users/tatu/Zotero/storage/5JUDFTTJ/creating-smarter-systems.html},
  note = {00000}
}

@book{gilchrist2016industry,
  title = {Industry 4.0: {{The Industrial Internet}} of {{Things}}},
  isbn = {978-1-4842-2047-4},
  url = {https://books.google.fi/books?id=YuOODAAAQBAJ},
  publisher = {{Apress}},
  date = {2016},
  author = {<NAME>.},
  note = {00066}
}

@book{buyya2016internet,
  title = {Internet of {{Things}}: {{Principles}} and {{Paradigms}}},
  isbn = {978-0-12-809347-4},
  url = {https://books.google.fi/books?id=_k11CwAAQBAJ},
  publisher = {{Elsevier Science}},
  date = {2016},
  author = {<NAME>. and <NAME>.},
  note = {00059}
}

@inproceedings{maSmartMeteorologicalService2017,
  title = {A Smart Meteorological Service Model Based on Big {{Data}}: {{A}} Value Creation Perspective},
  doi = {10.1109/GSIS.2017.8077722},
  shorttitle = {A Smart Meteorological Service Model Based on Big {{Data}}},
  abstract = {With the rapid development of cloud computing, the Internet of things, big data has become one of the hot spots of society, but also a major focus of applied research, made many service sectors to become data-driven organizations, which exploit the value of big data resources to gain competitive advantage. The meteorological department and the Internet online monitoring collected a large number of meteorological data, deeply develop meteorological data value by using big data analysis method, also by comparing the data and model analysis technology. Within this paper, a literature review, surveys and expert interviews were used in this research paradigm, it analyzed the meteorological observation data management service system, proposed a value-driven smart meteorological service model based on big data. The aim of this paper is to construct a value-driven smart meteorological big data service model that includes resource collaboration, technical collaboration, and service collaboration, optimize the meteorological forecast processes. This promotes meteorological related services products more fine, more accurate and longer forecast timeliness in meteorological disaster prevention and mitigation, public transportation, flood control and drought, agricultural production, transportation and other areas.},
  eventtitle = {2017 {{International Conference}} on {{Grey Systems}} and {{Intelligent Services}} ({{GSIS}})},
  booktitle = {2017 {{International Conference}} on {{Grey Systems}} and {{Intelligent Services}} ({{GSIS}})},
  date = {2017-08},
  pages = {299-305},
  keywords = {Big Data,big data analysis,cloud computing,data analysis,data management service system,data models,Data models,Economics,geophysics computing,Government,groupware,Industries,Internet of things,Internet online monitoring,meteorological data value,meteorological department,Meteorological Forecasting,meteorology,resource collaboration,service collaboration,Service Collaboration,Service Model,smart meteorological big data service model,technical collaboration,value creation,Weather forecasting,Web services},
  author = {<NAME>. and <NAME>.},
  file = {/Users/tatu/Zotero/storage/LFGUMWJ8/8077722.html},
  note = {00000}
}

@thesis{elovaaraAggregatingOPCUA2015,
  langid = {english},
  title = {Aggregating {{OPC UA Server}} for {{Remote Access}} to {{Agricultural Work Machines}}},
  url = {http://urn.fi/URN:NBN:fi:aalto-201509184356},
  abstract = {Agricultural machinery has improved rapidly during the last decades and the role of electronic controllers and sensors has increased. Simultaneously and partially because of this, the efficiency requirements concerning farming have grown more stringent. Information systems to help in farm management are already commonplace. Many work machines utilize the ISO 11783 communication protocol, through which a lot of data from the operation and internal state of a machine could be retrieved. However, this available data from agricultural work machines is not fully utilized. This thesis evaluates OPC UA aggregating servers as a centralized means to read and store the data available from multiple work machines.
 
 
This thesis builds on an earlier thesis where an OPC UA information model was developed for agricultural work machines utilizing the ISO 11783 communication protocol. First, a literature review was done to get a general view of the current state and the intended future of farm management systems, and to see how and where the data from the work machines can be utilized. Based on this and the previous work, the requirements for an aggregating server concentrating the information available from work machines running OPC UA servers were defined. A prototype aggregating server that is able to automatically transform the information from multiple ISO 11783 work machines to a unified view using a set of mapping rules was designed and implemented.
 
 
OPC UA aggregating servers were found to be viable technology for the centralized data monitoring and collection of ISO 11783 work machines. All relevant data exposed by the work machine OPC UA servers can also be accessed through the aggregating server. The mapping engine implemented on the aggregating server prototype can be extended to automatically map the information from other devices exposing themselves through OPC UA as well. The usefulness of an aggregating server increases if in the future OPC UA will be more commonly adopted and utilized by other agricultural equipment as well.},
  pagetotal = {68+7},
  institution = {{Aalto university}},
  urldate = {2018-04-23},
  date = {2015-08-24},
  author = {<NAME>},
  note = {00003}
}

@book{verdouwInternetThingsAgriculture2016a,
  title = {Internet of {{Things}} in Agriculture},
  volume = {11},
  abstract = {This literature review on Internet of Things (IoT) in agriculture and food, provides an overview of
existing applications, enabling technologies and main challenges ahead. The results of the review
show that this subject received attention by the scientific community from 2010 on and the number
of papers has increased since then. The literature on IoT in agriculture and food is very much
dominated by Asian scientists, especially from China. In other continents, the concept of IoT was up
to recently mainly adopted by non-agricultural scientists. The application area of food supply chains is
addressed most frequently, followed by arable farming. Most papers report the results of explorative
studies or they present IoT systems that are designed or implemented in prototypes and pilots. The
literature reviewed focuses on sensing and monitoring, while actuation and remote control is much
less addressed. The findings indicate that IoT is still in its infancy in the agriculture and food domain.
Applications are often fragmentary, lack seamless integration and especially more advanced solutions
are in an experimental stage of development. Important challenges to overcome this situation include
(i) integration of existing IoT solutions by open IoT architectures, platforms and standards,
(ii) upscaling the usage of interoperable IoT technologies beyond early adopters especially by the
simplification of existing solutions and make it more affordable for end users, and (iii) further
improvement of IoT technologies to ensure a broad usability in the diversity of the agri-food domain.},
  pagetotal = {1},
  date = {2016-12-01},
  author = {<NAME> <NAME> and <NAME>},
  doi = {10.1079/PAVSNNR201611035},
  note = {00003}
}

@article{talaveraReviewIoTApplications2017,
  title = {Review of {{IoT}} Applications in Agro-Industrial and Environmental Fields},
  volume = {142},
  issn = {0168-1699},
  url = {http://www.sciencedirect.com/science/article/pii/S0168169917304155},
  doi = {10.1016/j.compag.2017.09.015},
  abstract = {This paper reviews agro-industrial and environmental applications that are using Internet of Things (IoT). It is motivated by the need to identify application areas, trends, architectures and open challenges in these two fields. The underlying survey was developed following a systematic literature review using academic documents written in English and published in peer-reviewed venues from 2006 to 2016. Selected references were clustered into four application domains corresponding to: monitoring, control, logistics, and prediction. Implementation-specific details from each selected reference were compiled to create usage distributions of sensors, actuators, power sources, edge computing modules, communication technologies, storage solutions, and visualization strategies. Finally, the results from the review were compiled into an IoT architecture that represents a wide range of current solutions in agro-industrial and environmental fields.},
  journaltitle = {Computers and Electronics in Agriculture},
  shortjournal = {Computers and Electronics in Agriculture},
  date = {2017-11-01},
  pages = {283-297},
  keywords = {Internet of things,IoT,Agro-industry,Environmental monitoring,Systematic literature review},
  author = {Talavera, <NAME>, <NAME> Gómez, <NAME> and Culman, <NAME> and Aranda, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>},
  note = {00002}
}

@book{vermesanInternetThingsGlobal2011,
  location = {{Aalborg, UNKNOWN}},
  title = {Internet of {{Things}} - {{Global Technological}} and {{Societal Trends}} from {{Smart Environments}} and {{Spaces}} to {{Green Ict}}},
  isbn = {978-87-92982-88-9},
  url = {http://ebookcentral.proquest.com/lib/haaga/detail.action?docID=3400141},
  publisher = {{River Publishers}},
  date = {2011},
  keywords = {Computer networks -- Europe.,Information technology -- Europe.,Internet -- Europe.,Internet research -- Europe.,Ubiquitous computing -- Europe.},
  author = {<NAME> and <NAME>},
  note = {00000}
}

@misc{aHaastattelu2017,
  langid = {finnish},
  title = {Haastattelu 1},
  shorttitle = {H1},
  date = {2017-11-08},
  author = {<NAME>},
  editora = {<NAME>},
  editoratype = {collaborator},
  note = {Filename 171108\_1006.mp3
Duration 01:20:51
File format MP3 audio
File size 77,6 MB
Sample rate 44100}
}


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