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Electronics
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Intelligent Sensor Systems Applied in Smart Agriculture
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Intelligent Sensor Systems Applied in Smart Agriculture

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: 15 November 2024 | Viewed by 2364

Special Issue Editors

Prof. Dr. Heinz Bernhardt

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Guest Editor
Agricultural System Engineering, Technical University of Munich, 85354 Freising, Germany
Interests: smart farming; energy management; agricultural logistic
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Patrick Noack

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Guest Editor
Information Technology and IoT in Agriculture and Environment, University of Applied Sciences Weihenstephan Triesdorf, 91746 Weidenbach, Germany
Interests: sensor technology; smart farming

Special Issue Information

Dear Colleagues,

Smart farming sensor technology harnesses a diverse array of sensors, including soil, weather, GPS, and livestock monitoring devices, to systematically amass real-time, high-resolution data crucial for precision agriculture. These sensors are attuned to variables such as soil moisture, temperature, humidity, and meteorological conditions, enabling farmers to make empirically grounded decisions.

Paramount among its advantages is the realization of precision agriculture. By subjecting these data to meticulous analysis and employing them to delineate specific spatial and temporal zones within fields, farmers can calibrate irrigation, fertilization, and pest management strategies with pinpoint accuracy, effectuating augmented crop yields, curtailed resource outlays, and diminished operational expenditures.

Automation is integral to this paradigm. Autonomous machinery, finely calibrated through sensor-derived data, orchestrates farming operations such as seeding, weeding, and harvesting with unerring precision and efficiency. Concurrently, remote monitoring facilitated by smartphones or computer interfaces empowers farmers to vigilantly oversee operations, allowing for rapid responses to contingencies.

Advanced data analytics and machine learning algorithms underpin the processing and interpretation of sensor-generated data. This engenders predictive modeling, early-stage disease detection, and crop yield prediction, thus substantially augmenting the efficacy of farm management.

Furthermore, smart farming fosters energy efficiency via technologies like solar-powered sensors and precise irrigation systems, thereby mitigating the ecological footprint of agricultural practices. Livestock sensors serve as vanguards for animal welfare and productivity enhancement.

Notwithstanding its numerous merits, the implementation of smart farming technology necessitates sensible capital investments in infrastructure, data management protocols, and personnel training, concomitant with the resolution of pertinent issues concerning data security and privacy. Nonetheless, smart farming sensor technology constitutes a transformative force in agriculture, endowing it with an impression of sustainability, efficiency, and productivity hitherto unparalleled.

Prof. Dr. Heinz Bernhardt
Prof. Dr. Patrick Noack
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • precision agriculture
  • agricultural sensor networks
  • IoT (internet of things) in agriculture
  • sensor data analytics
  • remote monitoring
  • sustainable farming technologies

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Published Papers (2 papers)

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28 pages, 8356 KiB  
Article
Concept and Realisation of ISFET-Based Measurement Modules for Infield Soil Nutrient Analysis and Hydroponic Systems
by Vadim Riedel, Stefan Hinck, Edgar Peiter and Arno Ruckelshausen
Electronics 2024, 13(13), 2449; https://doi.org/10.3390/electronics13132449 - 22 Jun 2024
Cited by 1 | Viewed by 711
Abstract
Ion-selective field-effect transistors (ISFETs) offer potential as micro-sensors for in situ monitoring of complex target variables in real-time closed loop actions. This article presents the concept and realisation of application-specific ISFET-based measurement systems for two different agricultural domains: infield soil measurements and hydroponic [...] Read more.
Ion-selective field-effect transistors (ISFETs) offer potential as micro-sensors for in situ monitoring of complex target variables in real-time closed loop actions. This article presents the concept and realisation of application-specific ISFET-based measurement systems for two different agricultural domains: infield soil measurements and hydroponic systems. Commercially available ISFETs were integrated as multi-sensor modules as well as single-sensor units for the measurement of plant-available nutrients, such as H2PO4−, NO3−, K+ or NH4+, and pH-values. Moreover, application-relevant pH values as well as temperatures for calibration purposes were measured. ISFETs were selected according to the relevant measurement dynamics for the applications. For the development and testing procedures, a laboratory setup was built up. Supported by reference materials, the outputs of the ISFETs were evaluated with respect to stability under the influence of disturbance variables, reproducibility and settling time. The results were used to develop new readout electronics. Next to stability, conditioning and calibration processes were relevant. The micro-sensors were integrated in new application-specific mechatronic handling systems and process flows. The realisation and tests are presented as well as first measurements in outdoor fields and indoor hydroponic environments. Full article
(This article belongs to the Special Issue Intelligent Sensor Systems Applied in Smart Agriculture)
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26 pages, 10104 KiB  
Article
Validation Scores to Evaluate the Detection Capability of Sensor Systems Used for Autonomous Machines in Outdoor Environments
by Magnus Komesker, Christian Meltebrink, Stefan Ebenhöch, Yannick Zahner, Mirko Vlasic and Stefan Stiene
Electronics 2024, 13(12), 2396; https://doi.org/10.3390/electronics13122396 - 19 Jun 2024
Viewed by 1138
Abstract
The characterization of the detection capability assumes significance when the reliable monitoring of the region of interest by a non-contact sensor is a safety-relevant function. This paper introduces new validation scores that evaluate the detection capability of non-contact sensors intended to be applied [...] Read more.
The characterization of the detection capability assumes significance when the reliable monitoring of the region of interest by a non-contact sensor is a safety-relevant function. This paper introduces new validation scores that evaluate the detection capability of non-contact sensors intended to be applied to outdoor machines. The scores quantify, in terms of safety, the suitability of the sensor for the intended implementation in an environmental perception system of (highly) automated machines. This was achieved by developing an extension to the new Real Environment Detection Area (REDA) method and linking the methodology with the sensor standard IEC/TS 62998-1. The extension includes point-by-point and statistic-based error evaluation which leads to the Usability-Score, Availability-Score, and Reliability-Score. By applying the principle in the agricultural sector using ISO 18497 and linking this with data from a real outdoor test stand, it was possible to show that the validation scores offer a generic approach to quantify the detection capability and express this in a machine manufacturer-oriented manner. The findings of this study have significant implications for the advancement of safety-related sensor systems integrated into machines operating in complex environments. In order to achieve full implementation, it is necessary to define in the standards which score is required for each Performance Level (PL). Full article
(This article belongs to the Special Issue Intelligent Sensor Systems Applied in Smart Agriculture)
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