Implementation and applications of harvest fleet route planning

In order to support the growing global population, it is necessary to increase food production efficiency and at the same time reduce its negative environmental impacts. This can be achieved by integrating diverse strategies from different scientific disciplines. As agriculture is becoming more data-driven by the use of technologies such as the Internet of Things, the efficiency in agricultural operations can be optimised in a sustainable manner. Some field operations, such as harvesting, are more complex and have higher potential for improvement than others, as they involve multiple and diverse vehicles with capacity constraints that require coordination. This can be achieved by optimised route planning, which is a combinatorial optimisation problem. Several studies have proposed different approaches to solve the problem. However, these studies have mainly a theoretical computer science perspective and lack the system perspective that covers the practical implementation and applications of optimised route planning in all field operations, being harvesting an important example to focus on. This requires an interdisciplinary approach, which is the aim of this Ph.D. project.The research of this Ph.D. study examined how Internet of Things technologies are applied in arable farming in general, and in particular in optimised route planning. The technology perspective of the reviewing process provided the necessary knowledge to address the physical implementation of a harvest fleet route planning tool that aims to minimise the total harvest time. From the environmental point of view, the risk of soil compaction resulting from vehicle traffic during harvest operations was assessed by comparing recorded vehicle data with the optimised solution of the harvest fleet route planning system. The results showed a reduction in traffic, which demonstrates that these optimisation tools can be part of the soil compaction mitigation strategy of a farm. And from the economic perspective, the optimised route planner of an autonomous field robot was employed to evaluate the economic consequences of altering the route in selective harvesting. The results presented different scenarios where selective harvest was not economically profitable. The results also identified some cases where selective harvest has the potential to become profitable depending on grain price differences and operational costs. In conclusion, these different perspectives to harvest fleet route planning showed the necessity of assessing future implementation and potential applications through interdisciplinarity

EIP-AGRI Focus Group : Precision farming

Final report201

Emerging technologies applied to the agrifood sector

The sustainable development goals proposed by the 2030 Agenda include: putting an end to hunger, achieving food security, improving nutrition and promoting sustainable agriculture. Many different initiatives will be required to meet these challenges, but they undoubtedly require the application of the latest scientific and technological breakthroughs to transform a sector that is strategic for our society.Objectius de Desenvolupament Sostenible::2 - Fam zeroObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

Next Generation Cloud Computing: New Trends and Research Directions

The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

Inferring Complex Activities for Context-aware Systems within Smart Environments

The rising ageing population worldwide and the prevalence of age-related conditions such as physical fragility, mental impairments and chronic diseases have significantly impacted the quality of life and caused a shortage of health and care services. Over-stretched healthcare providers are leading to a paradigm shift in public healthcare provisioning. Thus, Ambient Assisted Living (AAL) using Smart Homes (SH) technologies has been rigorously investigated to help address the aforementioned problems. Human Activity Recognition (HAR) is a critical component in AAL systems which enables applications such as just-in-time assistance, behaviour analysis, anomalies detection and emergency notifications. This thesis is aimed at investigating challenges faced in accurately recognising Activities of Daily Living (ADLs) performed by single or multiple inhabitants within smart environments. Specifically, this thesis explores five complementary research challenges in HAR. The first study contributes to knowledge by developing a semantic-enabled data segmentation approach with user-preferences. The second study takes the segmented set of sensor data to investigate and recognise human ADLs at multi-granular action level; coarse- and fine-grained action level. At the coarse-grained actions level, semantic relationships between the sensor, object and ADLs are deduced, whereas, at fine-grained action level, object usage at the satisfactory threshold with the evidence fused from multimodal sensor data is leveraged to verify the intended actions. Moreover, due to imprecise/vague interpretations of multimodal sensors and data fusion challenges, fuzzy set theory and fuzzy web ontology language (fuzzy-OWL) are leveraged. The third study focuses on incorporating uncertainties caused in HAR due to factors such as technological failure, object malfunction, and human errors. Hence, existing studies uncertainty theories and approaches are analysed and based on the findings, probabilistic ontology (PR-OWL) based HAR approach is proposed. The fourth study extends the first three studies to distinguish activities conducted by more than one inhabitant in a shared smart environment with the use of discriminative sensor-based techniques and time-series pattern analysis. The final study investigates in a suitable system architecture with a real-time smart environment tailored to AAL system and proposes microservices architecture with sensor-based off-the-shelf and bespoke sensing methods. The initial semantic-enabled data segmentation study was evaluated with 100% and 97.8% accuracy to segment sensor events under single and mixed activities scenarios. However, the average classification time taken to segment each sensor events have suffered from 3971ms and 62183ms for single and mixed activities scenarios, respectively. The second study to detect fine-grained-level user actions was evaluated with 30 and 153 fuzzy rules to detect two fine-grained movements with a pre-collected dataset from the real-time smart environment. The result of the second study indicate good average accuracy of 83.33% and 100% but with the high average duration of 24648ms and 105318ms, and posing further challenges for the scalability of fusion rule creations. The third study was evaluated by incorporating PR-OWL ontology with ADL ontologies and Semantic-Sensor-Network (SSN) ontology to define four types of uncertainties presented in the kitchen-based activity. The fourth study illustrated a case study to extended single-user AR to multi-user AR by combining RFID tags and fingerprint sensors discriminative sensors to identify and associate user actions with the aid of time-series analysis. The last study responds to the computations and performance requirements for the four studies by analysing and proposing microservices-based system architecture for AAL system. A future research investigation towards adopting fog/edge computing paradigms from cloud computing is discussed for higher availability, reduced network traffic/energy, cost, and creating a decentralised system. As a result of the five studies, this thesis develops a knowledge-driven framework to estimate and recognise multi-user activities at fine-grained level user actions. This framework integrates three complementary ontologies to conceptualise factual, fuzzy and uncertainties in the environment/ADLs, time-series analysis and discriminative sensing environment. Moreover, a distributed software architecture, multimodal sensor-based hardware prototypes, and other supportive utility tools such as simulator and synthetic ADL data generator for the experimentation were developed to support the evaluation of the proposed approaches. The distributed system is platform-independent and currently supported by an Android mobile application and web-browser based client interfaces for retrieving information such as live sensor events and HAR results

Raamistik mobiilsete asjade veebile

Internet on oma arengus läbi aastate jõudnud järgmisse evolutsioonietappi - asjade internetti (ingl Internet of Things, lüh IoT). IoT ei tähista ühtainsat tehnoloogiat, see võimaldab eri seadmeil - arvutid, mobiiltelefonid, autod, kodumasinad, loomad, virtuaalsensorid, jne - omavahel üle Interneti suhelda, vajamata seejuures pidevat inimesepoolset seadistamist ja juhtimist. Mobiilseadmetest nagu näiteks nutitelefon ja tahvelarvuti on saanud meie igapäevased kaaslased ning oma mitmekülgse võimekusega on nad motiveerinud teadustegevust mobiilse IoT vallas. Nutitelefonid kätkevad endas võimekaid protsessoreid ja 3G/4G tehnoloogiatel põhinevaid internetiühendusi. Kuid kui kasutada seadmeid järjepanu täisvõimekusel, tühjeneb mobiili aku kiirelt. Doktoritöö esitleb energiasäästlikku, kergekaalulist mobiilsete veebiteenuste raamistikku anduriandmete kogumiseks, kasutades kergemaid, energiasäästlikumaid suhtlustprotokolle, mis on IoT keskkonnale sobilikumad. Doktoritöö käsitleb põhjalikult energia kokkuhoidu mobiilteenuste majutamisel. Töö käigus loodud raamistikud on kontseptsiooni tõestamiseks katsetatud mitmetes juhtumiuuringutes päris seadmetega.The Internet has evolved, over the years, from just being the Internet to become the Internet of Things (IoT), the next step in its evolution. IoT is not a single technology and it enables about everything from computers, mobile phones, cars, appliances, animals, virtual sensors, etc. that connect and interact with each other over the Internet to function free from human interaction. Mobile devices like the Smartphone and tablet PC have now become essential to everyday life and with extended capabilities have motivated research related to the mobile Internet of Things. Although, the recently developed Smartphones enjoy the high performance and high speed 3G/4G mobile Internet data transmission services, such high speed performances quickly drain the battery power of the mobile device. This thesis presents an energy efficient lightweight mobile Web service provisioning framework for mobile sensing utilizing the protocols that were designed for the constrained IoT environment. Lightweight protocols provide an energy efficient way of communication. Finally, this thesis highlights the energy conservation of the mobile Web service provisioning, the developed framework, extensively. Several case studies with the use of the proposed framework were implemented on real devices and has been thoroughly tested as a proof-of-concept.https://www.ester.ee/record=b522498

A Novel Variable Geometry based Planar Inductor Design for Wireless Charging Application

In this thesis, the performance, modelling and application of a planar electromagnetic coil are discussed. Due to the small size profiles and their non‐contact nature, planar coils are widely used due to their simple and basic design. The uncertain parameters have been identified and simulated using ANSYS that has been run utilising a newly developed MATLAB code. This code has made it possible to run thousands of trials without the need to manually input the various parameters for each run. This has facilitated the process of obtaining all the probable solutions within the defined range of properties. The optimum and robust design properties were then determined. The thesis discusses the experimentation and the finite element modelling (FEM) performed for developing the design of planar coils and used in wireless chargers. In addition, the thesis investigates the performance of various topologies of planar coils when they are used in wireless chargers. The ANSYS Maxwell FEM package has been used to analyse the models while varying the topologies of the coils. For this purpose, different models in FEM were constructed and then tested with topologies such as circular, square and hexagon coil configurations. The described methodology is considered as an effective way for obtaining maximum Power transfer efficiency (PTE) with a certain distance on planar coils with better performance. The explored designs studies are, namely: (1) Optimization of Planar Coil Using Multi-core, (2) planar coil with an Orthogonal Flux Guide, (3) Using the Variable Geometry in a Planar coil for an Optimised Performance by using the robust design method, (4) Design and Integration of Planar coil on wireless charger. In the first design study, the aim is to present the behaviour of a newly developed planar coil, built from a Mu-metal, via simulation. The structure consists of an excitation coil, sensing coils and three ferromagnetic cores 2 located on the top, middle and bottom sections of the coil in order to concentrate the field using the iterative optimisation technique. Magnetic materials have characteristics which allows them to influence the magnetic field in its environment. The second design study presents the optimal geometry and material selection for the planar with an Orthogonal Flux Guide. The study demonstrates the optimising of the materials and geometry of the coil that provides savings in terms of material usage as well as the employed electric current to produce an equivalent magnetic field. The third design study presents the variable geometry in a planar inductor to obtain the optimised performance. The study has provided the optimum and robust design parameters in terms of different topologies such as circular, square and hexagon coil configurations and then tested, Once the best topology is chosen based on performance. The originality of the work is evident through the randomisation of the parameters using the developed MATLAB code and the optimisation of the joint performance under defined conditions. Finally, the fourth design study presents the development of the planar coil applications. Three shapes of coils are designed and experimented to calculate the inductance and the maximum power transfer efficiency (PTW) over various spacing distances and frequency