Farming the Web of Things

Taylor, Kerry; Griffith, Colin; Lefort, Laurent; Gaire, Raj; Compton, Michael; Wark, Tim; Lamb, David; Falzon, Greg; Trotter, Mark

doi:10.1109/mis.2013.102

Cited by 67 publications

(40 citation statements)

References 8 publications

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“…For example, semantic technologies are used in the home automation prototype system for monitoring and controlling heating and air conditioning [109]. A smart farming system is proposed in [110], where Global Sensor Networks (GSN) middleware and SSN ontologies are utilized to automate monitoring and controlling of farming activities. Zhou et al [111] propose semantic modeling for facilitating demand response optimizations in smart grids with automated real-time load prediction and curtailment.…”

Section: Related Work About Semantic Technologies For Pervasive Compumentioning

confidence: 99%

Lightweight data and knowledge exchange for pervasive environments1

2017

AIS

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Pervasive environments are physical spaces saturated with devices collecting data, controlling the environment, and interacting with users. These environments support human users in their everyday tasks so that the users can focus on their own tasks and access services and resources whenever and wherever they want. Such environments are also called smart spaces. Knowledgebased systems would enable realizing a variety of intelligent applications for pervasive environments. Generally, such systems recognize the situation in the environment from sensor data and utilize automated reasoning techniques to respond to the situation and the needs of the users.However, building knowledge-based systems for pervasive environments presents challenges. This dissertation focuses on the challenge of data and knowledge representations. Knowledgebased systems utilize expressive knowledge representations that are verbose and require sufficient resources in order to use them. Most devices in pervasive environments cannot handle these representations as the devices have limited resources for computation, storage, and communication. The main aim of this dissertation is to tackle this challenge. That is, on the one hand, pervasive environments demand data and knowledge representations that do not require many resources from the resource-constrained devices; and on the other hand, the representations should be compatible with the knowledge-based systems. Specifically, a general solution is required that enables many applications to use the same data with minimal effort from application developers.This dissertation presents a novel representation, Entity Notation (EN), to tackle these challenges. EN is designed as a general lightweight representation for data and knowledge. EN expresses entities, their properties, and property values. This structure resembles the triple structure of Resource Description Framework (RDF) and Web Ontology Language (OWL). Hence, sensor data in EN syntax can be transformed into common knowledge models in a straightforward manner and utilized with ease by knowledge-based systems. EN Schema is designed for transferring advanced knowledge models. Moreover, EN also offers an approach to shorten the format with templates and prefixes. This way, EN can be utilized by resourceconstrained devices and environments. Our evaluation verifies that small devices can utilize EN to transfer data and knowledge to devices realizing intelligent functions, such as inference. Moreover, the expressive power of EN is comparable with the alternative representations. Finally, resource consumption is verified by prototypes. Based on the evaluation, we can conclude that EN can facilitate harnessing the full potential of pervasive environments.Keywords: Entity Notation, knowledge-based systems, ontology, reasoning, Resource Description Framework, resourceconstrained devices, semantics Su, Xiang, Kevyen datan ja tietämyksen esitystavat jokapaikan tietotekniikan sovelluksille.Oulun yliopiston tutkijakoulu; Oulun yliopisto, Tieto-...

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Section: Related Work About Semantic Technologies For Pervasive Compumentioning

confidence: 99%

Lightweight data and knowledge exchange for pervasive environments1

2017

AIS

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“…There are related work that does incorporate semantic technologies such as AGROVOC [16], Agri-IoT [17], CSIRO's Kirby Farm project [18] and the ThinkHome smart home system [6]. AGROVOC is a formal vocabulary in RDF form that allows for the linking of agricultural data.…”

Section: Related Workmentioning

confidence: 99%

“…However, the focus is predominantly on energy consumption and power management as opposed to water conservation. The Agri-IoT project and CSIRO's Kirby Farm project are semantic web and IoT-based frameworks that are capable of processing multiple data streams for more effective agricultural management [17,18]. These projects incorporates linked data from multiple data points, including sensed, government and environmental web-based data, for informed and accurate event detection and decision making by farmers.…”

Section: Related Workmentioning

confidence: 99%

Semantic IoT: Intelligent Water Management for Efficient Urban Outdoor Water Conservation

Myers

Mohring

Andersen

2017

Lecture Notes in Computer Science

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“…Developments in mobile devices, data stored on remote cloud servers, and high‐speed broadband networks will allow emerging infrastructure to develop new services which can integrate both local data from the farm and integrate with external information such as weather or price forecasts (Taylor et al. ).…”

Section: Enabling Technologiesmentioning

confidence: 99%

Prospects for yield improvement in the Australian wheat industry: a perspective

Robertson

Kirkegaard

Rebetzke

et al. 2016

Food and Energy Security

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For the Australian grains industry, recent progress in wheat yield (the dominant crop) due to genetic improvement and advances in agronomy is assessed, and we propose some of the emerging technologies that are likely to contribute to yield gain in the medium (10-20 years) term. Advances in yield will be underpinned by new genetics tailored to agronomic technologies with progress in water-limited yield potential expected to increase from current levels of ca. 0.5% per year. This increase will be achieved by selecting traits with greater water productivity, tolerance to frost and high temperature, and resistance to a range of soil constraints through access to novel genetic diversity, and deployment of targeted biotechnology and tools to improve confidence in phenotyping and environmental characterization. Hybrid cereals should halve the time to cultivar delivery to less than 6 years while allowing for more rapid incorporation and delivery of new traits, and capacity to exploit heterosis. There will be better adoption of recent technologies (such as variable-rate technology, soil testing, soil amelioration, and timely sowing) with the potential to increase yield by 10-80%. Novel technology packages such as earlier sowing systems will be enabled by improvements in integrated weed management, seasonal climate forecasting, plastic mulches, materials science, information and communication technologies, and weather monitoring and soil sensing. With a conservative assumption about maintaining the current rate of genetic progress at 0.5% per year, ongoing adoption of current and new agronomic technologies, continuing investment in R&D, and farm consolidation, at a whole industry level, annual gains in wheat yields of around 20 kg/ha (0.8-1.0%) are feasible over the next 20 years. These gains are likely to be attenuated by only a modest impact (<10% reduction) on crop yield potential due to the negative impacts of climate change. 108

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Farming the Web of Things

Cited by 67 publications

References 8 publications

Lightweight data and knowledge exchange for pervasive environments1

Lightweight data and knowledge exchange for pervasive environments1

Semantic IoT: Intelligent Water Management for Efficient Urban Outdoor Water Conservation

Prospects for yield improvement in the Australian wheat industry: a perspective

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