A novel microclimate forecasting system architecture integrating GPS measurements and meteorological-sensor data

Zinas, Nicholas; Kontogiannis, Sotirios; Kokkonis, George; Pikridas, Christos

doi:10.1145/2490257.2490282

Cited by 9 publications

(6 citation statements)

References 4 publications

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“…Vity-stress system and protocol experimental scenario included the deployment of five pieces of Vity-stress sensory equipment as illustrated in Figure 3, in the 2.83 hectare viticulture field of debina vine variety [28], at the area of Zitsa, Ioannina Greece, owned by the author Dr. Kontogiannis. The vineyard consisted of lanes that are 100 m long with inter-lane distances of 1.60-1.80 m. The purpose of this scenario was to test the operation of the VSP, and determined the maximum coverage area.…”

Section: Experimental Scenario and Results Of The Vity-stress Protocolmentioning

confidence: 99%

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A Proposed Low-Cost Viticulture Stress Framework for Table Grape Varieties

Kontogiannis

Asiminidis

2020

IoT

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Climate change significantly affects viticulture by reducing the production yield and the quality characteristics of its final products. In some observed cases, the consequences of climate outages such as droughts, hail and floods are absolutely devastating for the farmers and the sustained local economies. Hence, it is essential to develop new in implementation monitoring solutions that offer remote real-time surveillance, alert triggering, minimum maintenance and automated generation of incident alerts with precision responses. This paper presents a new framework and a system for vine stress monitoring called Vity-stress. The Vity-stress framework combines field measurements with precise viticulture suggestions and stress avoidance planning. The key points of the proposed framework’s system are that it is easy to develop, easy to maintain and cheap to implement applicability. Focusing on the Mediterranean cultivated table grape varieties that are strongly affected by climate change, we propose a new stress conditions monitoring system to support our framework. The proposition includes distributed field located sensors and a novel camera module implementing deep neural network algorithms to detect stress indicators. Additionally, a new wireless sensor network supported by the iBeacon protocol has been developed. The results of the sensory measurements’ data logging and imposed image detection process’s evaluation shows that the proposed system can successfully detect different stress levels in vineyards, which in turn can allow producers to identify specific areas for irrigation, thereby saving water, energy and time.

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Section: Experimental Scenario and Results Of The Vity-stress Protocolmentioning

confidence: 99%

“…This is important for the detection of either stressful conditions or disease prosperous ones. Letting aside meteorological stations operating and providing micro-climate area predictions [28,29], this section focuses only on stump level vineyard condition monitoring sensors and metrics.…”

Section: Viticulture Sensors and Metricsmentioning

confidence: 99%

A Proposed Low-Cost Viticulture Stress Framework for Table Grape Varieties

Kontogiannis

Asiminidis

2020

IoT

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“…Finally, the authors of [49] presented a set of tools used for partitioning viticulture areas in Greece and post-processing data analysis of meteo station sensory measurements in the vicinity of these vine areas. In addition to precision viticulture treatments and DSS systems with inputs from sparsely located meteorological base stations, advancements in IoT and cloud technologies can provide new advanced Decision Support Systems (DSS) capable of better than micro-climate monitoring using dense monitoring stations for less than 2km sensory measurements acquisition [50]. Such systems can collect environmental data even at the plant-vine level using cheap IoT meteorological stations that aid farmers in making tactical and operational decisions.…”

Section: Downy Mildew Forecasting Dss Systemsmentioning

confidence: 99%

“…The meteorological station's field placements (see Figure 2d) usually follow a dense micro-climate grid monitoring approach of 1-1.5 km of coverage radius [50]. LoRaWAN meteorological stations also operate autonomously.…”

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confidence: 99%

Proposed Fuzzy-Stranded-Neural Network Model That Utilizes IoT Plant-Level Sensory Monitoring and Distributed Services for the Early Detection of Downy Mildew in Viticulture

Kontogiannis,

Koundouras,

Pikridas

2024

Computers

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Novel monitoring architecture approaches are required to detect viticulture diseases early. Existing micro-climate decision support systems can only cope with late detection from empirical and semi-empirical models that provide less accurate results. Such models cannot alleviate precision viticulture planning and pesticide control actions, providing early reconnaissances that may trigger interventions. This paper presents a new plant-level monitoring architecture called thingsAI. The proposed system utilizes low-cost, autonomous, easy-to-install IoT sensors for vine-level monitoring, utilizing the low-power LoRaWAN protocol for sensory measurement acquisition. Facilitated by a distributed cloud architecture and open-source user interfaces, it provides state-of-the-art deep learning inference services and decision support interfaces. This paper also presents a new deep learning detection algorithm based on supervised fuzzy annotation processes, targeting downy mildew disease detection and, therefore, planning early interventions. The authors tested their proposed system and deep learning model on the grape variety of protected designation of origin called debina, cultivated in Zitsa, Greece. From their experimental results, the authors show that their proposed model can detect vine locations and timely breakpoints of mildew occurrences, which farmers can use as input for targeted intervention efforts.

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“…Most of them monitor the environmental conditions inside and outside the beehive. The conditions that are often sensed are temperature, humidity, luminosity inside and outside the hive, as well as micro-climate environmental conditions including readings of rainfall, wind speed and atmospheric pressure [28]. In addition, there are no known systems in the literature that can diagnose diseases and bee illnesses, such as varroa mites and produce alerts.…”

Section: Iot Beehive Conditions Monitoring Systemsmentioning

confidence: 99%

An Internet of Things-Based Low-Power Integrated Beekeeping Safety and Conditions Monitoring System

Kontogiannis

2019

Inventions

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This paper proposes a holistic management and control system for the apiculture industry (Integrated Beekeeping System of holistic Management and Control – IBSMC). This integrated beehive array system mainly focuses on the regulation of bees living conditions, targeting both minimizing bee swarm mortality and maximizing productivity. Within the proposed IBSMC system architecture, additional security functionalities are implemented for bee monitoring, low energy consumption and incidents response. As a complete unit, the proposed IBSMC system is both a hive conditions monitoring and safety system. It communicates with the outer world using low power RF data transmission and the LoRaWAN transceivers. This paper presents the proposed IBSMC architecture consisting of new beehive cells embedded with functionalities for integrated conditions regulation and security provisions, as well as the communication protocols used for facility-conditions management, incidents’ acquisition and incidents’ response.

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A novel microclimate forecasting system architecture integrating GPS measurements and meteorological-sensor data

Cited by 9 publications

References 4 publications

A Proposed Low-Cost Viticulture Stress Framework for Table Grape Varieties

A Proposed Low-Cost Viticulture Stress Framework for Table Grape Varieties

Proposed Fuzzy-Stranded-Neural Network Model That Utilizes IoT Plant-Level Sensory Monitoring and Distributed Services for the Early Detection of Downy Mildew in Viticulture

An Internet of Things-Based Low-Power Integrated Beekeeping Safety and Conditions Monitoring System

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