Advances in IoT and Smart Sensors for Remote Sensing and Agriculture Applications

Ullo, Silvia Liberata; Sinha, G. R.

doi:10.3390/rs13132585

Cited by 62 publications

(18 citation statements)

References 58 publications

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“…Differently, while IoT seems widely analyzed by academics (Dias et al, 2019;Martinho, 2020;Morris et al, 2017;Ullo and Sinha, 2021), practitioners focus on specific aspects of this research field, such as the development of smart types of equipment and sensors. This means patents capable of automating harvesting stages, monitoring environmental parameters or smart systems with 5G network technology for connecting and exchanging data in agricultural fields.…”

Section: Discussionmentioning

confidence: 99%

“…Differently, while IoT seems widely analyzed by academics (Dias et al. , 2019; Martinho, 2020; Morris et al.…”

Section: Discussionmentioning

confidence: 99%

“…For example, AI-enabled sensors represent valuable instruments in agriculture. Along with the Internet of things (IoT) technology, they support weather and soil quality assessment, crop monitoring, the use of robots for harvesting and weeding (Ullo and Sinha, 2021). Smart technologies, including IoT and augmented reality, will be able to enhance the production of farm crops and livestock, as autonomous IoT systems will control the resources effectively, boosting their utility and assessing products quality.…”

Section: Introductionmentioning

confidence: 99%

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Exploring agricultural entrepreneurship and new technologies: academic and practitioners' views

Secinaro¹,

Mas²,

Massaro³

et al. 2021

BFJ

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PurposeThis paper investigates the relationship between agricultural entrepreneurship (AE) and new technologies using academic and practitioners' perspectives to understand how new technologies such as artificial intelligence (AI), machine learning and augmented reality can promote agri-businesses.Design/methodology/approachThe paper adopts a content and thematic analysis of 325 academic sources extracted from the Scopus database and 683 patents retrieved from the European Patent Office (EPO) dataset. Additionally, the research applies the Kruskal–Wallis test as a non-parametric test for evaluating differences in the main concepts discussed in the two sources.FindingsThe academic and practitioners' debate highlights a trading zone among the two streams. patents' analysis from the EPO reveals four main common themes as a new business that benefits from AI in weather predictions, new smart and intelligent ways to monitor crops, new businesses that use clouds to control plant's humidity. The analysis of Scopus's sources demonstrates theoretical approaches related to the technology acceptance model (TAM) and practical strategies in terms of entrepreneurial skills to support the agricultural sector. However, barriers among the two streams of sources exist in innovation management and scale-up entrepreneurial initiatives.Research limitations/implicationsRegarding implications, the authors aim to connect academic and practitioners' views by understanding the new potential innovation applications and the connected new research avenues. Limitations might arise from the sources used to develop our analysis.Originality/valueThe paper is novel because it investigates the issues arising from the relationship between AE and new technologies by examining original validated patents released by practitioners and approved by the EPO, rather than reviewing blogs or the financial press. This leads to a holistic understanding of the impact of tangible practices among agricultural entrepreneurs. The results support the view that new trading zones and case studies are needed to highlight and show the positive impact of technologies in this field. The authors argue that practitioners require scholars to reduce the ambiguity between AE and its expected results, leading to investments to boost new agricultural business ideas.

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Section: Discussionmentioning

confidence: 99%

“…Differently, while IoT seems widely analyzed by academics (Dias et al. , 2019; Martinho, 2020; Morris et al.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploring agricultural entrepreneurship and new technologies: academic and practitioners' views

Secinaro¹,

Mas²,

Massaro³

et al. 2021

BFJ

View full text Add to dashboard Cite

show abstract

“…This centralized architecture is not a practical solution for the IoT system that increases by billions every year. References [15,16] aimed to study lightweight learning methods to optimize the performance of the LoRaWAN technology. These studies compared nodes using multi-armed bandit (MAB) as a lightweight learning method for a decentralized optimization of the channel choice.…”

Section: Literature Reviewmentioning

confidence: 99%

Re-Learning EXP3 Multi-Armed Bandit Algorithm for Enhancing the Massive IoT-LoRaWAN Network Performance

Almarzoqi

Yahya

Matar

et al. 2022

Sensors

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Long-Range Wide Area Network (LoRaWAN) is an open-source protocol for the standard Internet of Things (IoT) Low Power Wide Area Network (LPWAN). This work’s focal point is the LoRa Multi-Armed Bandit decentralized decision-making solution. The contribution of this paper is to study the effect of the re-learning EXP3 Multi-Armed Bandit (MAB) algorithm with previous experts’ advice on the LoRaWAN network performance. LoRa smart node has a self-managed EXP3 algorithm for choosing and updating the transmission parameters based on its observation. The best parameter choice needs previously associated distribution advice (expert) before updating different choices for confidence. The paper proposes a new approach to study the effects of combined expert distribution for each transmission parameter on the LoRaWAN network performance. The successful transmission of the packet with optimized power consumption is the pivot of this paper. The validation of the simulation result has proven that combined expert distribution improves LoRaWAN network’s performance in terms of data throughput and power consumption.

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“…Applications of the intelligent approach in agriculture include the use of many types of sensors to monitor and control various environmental and production parameters, such as temperature, humidity, soil quality, pollution and quality of air, surface and groundwater, sunlight and many more [40]. This is to maximize harvest as well as other agricultural production.…”

Section: Smart Agriculturementioning

confidence: 99%

BelBuk System—Smart Logistics for Sustainable City Development in Terms of the Deficit of a Chemical Fertilizers

Grunt¹,

Błażejewski

Pecolt

et al. 2022

Energies

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Purpose: This paper presents an aspect of asset tracking and storage conditions. This paper aims to fill the gap in the development of Industry 4.0 in terms of fully digital asset tracking to be implemented by medium and large-size manufacturing and logistics facilities. The article presents an innovative technology for the remote monitoring of chemical raw materials, including fertilizers, during their storage and transport from the place of manufacture to the local distributor or recipient. Methods: The method assumes the monitoring and identification of special transport bags, so-called “big-bags,” through embedded RFID tags or LEB labels and monitoring the key parameters of their content, i.e., temperature, humidity, insolation, and pressure, using a measuring micro-station that is placed in the transported raw material. Results: The automation of inference based on the collected information about the phenomenon in question (the distribution of parameters: pressure, temperature, and humidity), and expert knowledge, allows the creation of an advisory system prototype indicating how to manage the measuring devices. Conclusions: No similar solution in the field of monitoring environmental parameters has been implemented in the Polish market. The developed system enables the monitoring of 10,000 pieces of big bags in at least 30 locations simultaneously.

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Advances in IoT and Smart Sensors for Remote Sensing and Agriculture Applications

Cited by 62 publications

References 58 publications

Exploring agricultural entrepreneurship and new technologies: academic and practitioners' views

Exploring agricultural entrepreneurship and new technologies: academic and practitioners' views

Re-Learning EXP3 Multi-Armed Bandit Algorithm for Enhancing the Massive IoT-LoRaWAN Network Performance

BelBuk System—Smart Logistics for Sustainable City Development in Terms of the Deficit of a Chemical Fertilizers

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