State of the Art in Internet of Things Standards and Protocols for Precision Agriculture with an Approach to Semantic Interoperability

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper appears to be well-structured and covers critical aspects of IoT technology integration in precision agriculture, addressing interoperability challenges, standards, protocols, and their practical applications. I have the following concerns:

1. The lack of shared communication standards among IoT devices in precision agriculture creates significant challenges. Different sensors and systems use heterogeneous data formats, making it difficult to analyze and integrate data effectively. E.g., manufacturers often provide proprietary software for their devices, which limits cross-platform compatibility and creates silos of information.

 

2. The architecture relies on a separate "connector" for each sensor type, leading to scalability and maintenance challenges as more sensor types are added. The authors can use machine learning or pattern recognition algorithms to classify incoming data and map it to the standard automatically.

 

3. While the OGC SensorThings standard meets most system requirements, its complexity and lack of intuitive implementation make it challenging for users without prior technical knowledge.

Author Response

The paper appears to be well-structured and covers critical aspects of IoT technology integration in precision agriculture, addressing interoperability challenges, standards, protocols, and their practical applications. I have the following concerns:

Thank you for your positive comment regarding the structure of our paper and for appreciating the discussion of the critical aspects of integrating IoT technology in precision agriculture. Below, we respond to your concerns point by point, providing clarification and additional details where necessary.

 

1. The lack of shared communication standards among IoT devices in precision agriculture creates significant challenges. Different sensors and systems use heterogeneous data formats, making it difficult to analyze and integrate data effectively. E.g., manufacturers often provide proprietary software for their devices, which limits cross-platform compatibility and creates silos of information.

Thanks for the comment. The main purpose of the article is precisely to address the issue highlighted by the reviewer and to propose solutions and guidelines to overcome the limitations related to cross-platform compatibility.  Specifically, in our work we propose the use of connectors as an approach to improve integration between heterogeneous systems. Such connectors were tested on two different commercial solutions, Waspmote Libellium and Digital Matter SensorData.

 

2. The architecture relies on a separate "connector" for each sensor type, leading to scalability and maintenance challenges as more sensor types are added. The authors can use machine learning or pattern recognition algorithms to classify incoming data and map it to the standard automatically.

We thank the reviewer for raising this issue, which represents an opportunity to improve our work. We would like to emphasize that the proposed solution involves the use of one connector per sensor family. This means that, in a real deployment, a single connector could be used to manage a multiplicity of devices belonging to the same family, such as Libellium devices, while another connector could be used to manage several devices of the Digital Matter family, and so on. This approach significantly reduces the total number of connectors needed compared to single device management. However, we fully agree with the reviewer that the adoption of machine learning or pattern recognition algorithms could further improve the scalability of the system. In response to this comment, we have added a paragraph in the section “7. Discussion” to describe this possible development. The text added is as follows:

“Furthermore, as demonstrated in the literature, the integration of machine learning algorithms for pattern recognition in incoming data represents an opportunity to improve the scalability and interoperability of the system [ 98 , 99]. These algorithms could be employed to automatically  classify data from various sensors and map it in real time to the required standard, thereby reducing the need to manually design specific connectors for each sensor family [ 100 ]. This approach could not only enhance operational efficiency but also lower maintenance costs and facilitate the expansion of the system to accommodate new devices. The future goal is to develop a wider variety of connectors to support the majority of commonly used sensors in the agriculture market and to integrate Natural Language Processing algorithms to enhance the scalability of the proposed architecture [101].”

3. While the OGC SensorThings standard meets most system requirements, its complexity and lack of intuitive implementation make it challenging for users without prior technical knowledge.

We thank the Reviewer for pointing out a potential critical issue related to the adoption of the OGC SensorThings standard. We understand that complexity may be an obstacle for some users, particularly those without prior technical knowledge. However, we feel it is important to emphasise that the OGC SensorThings standard offers many advantages, including interoperability between IoT devices from different manufacturers thanks to a standardised data model and open protocols. This facilitates the development of heterogeneous and scalable systems. Furthermore, the standard is designed to handle real-time data streams from a large number of sensors, making it particularly suitable for complex applications such as precision agriculture. Finally, as we answered in the previous point, we are working on including the latest Natural Language Processing (NLP) algorithms in future work to further simplify the understanding of the standard for non-expert users and to improve the scalability of the system.

Reviewer 2 Report

Comments and Suggestions for Authors

In the paper  “State of the Art in IoT Standards and Protocols for Precision Agriculture and New Interoperable Architecture Proposal”, the authors analyze and compare the available communication protocols and standards for the smart agriculture sector.

The research challenges and problem formulation are relatively clear, but I would suggest changing the order of the research questions: RQ2, the requirements should be the starting point because the protocols and standards should be chosen having the requirements in mind.

Section 3 is just a description of current protocols, which is more suitable for a book chapter or lecture notes than for a scientific paper as it does not bring any new knowledge. For example, a more detailed comparison table that also includes the answers for RQ2 (and maybe RQ4) could be added. Each protocol could be analyzed and specified to which degree it fulfills the requirements of the precision agriculture sector.

Table 1 contains too much text in my opinion and does not correlate to the specifications of this field. E.g. The REST architecture support, why is it relevant to this field? Why not compare the protocols in terms of the requirements identified in lines 410-417?

Why is MQTT-SN not considered in this survey? Precision architecture also implies network sensors, thus this protocol may be of interest.

The title of Table 2 refers to 3 protocols, but the table contains 5. Again, the table does not bring any new information as it is not correlated to the requirements.

Similarly, in section 4, Table 5 does not make a correlation between the standards and the requirements from lines 410-417 as it might be suggested in paragraph 4.2. Why are these the key features? It is not clearly explained.

Figure 2 is just reproduced from another paper and the same figure is also available on Wikipedia, which may be subject to copyright issues. I do not understand the need for such a long section 5, as it does not contain any remarkable contribution and the main ideas could be presented in some paragraphs.

The actual core of the paper, presenting the main contributions of this paper starts at section 6, which makes the introductory part a little too long compared to the core. I suggest the compression of sections 3, 4, and 5 into only one section, as in the current form these sections do not bring new knowledge and do not represent the core of this research. The section could be called Protocols and Standards, for example. In this unified section, starting from the requirements representing the RQ2 answers, all the mentioned protocols and standards are to be analyzed and compared.

Although Table 8 is very useful, a supplementary table analyzing the open-source software in correlation with the answers for RQ4 should be added.

The steps from Section 7 could also be represented by a state diagram, especially the ones in lines 892-905. For the database described in the same section, a relational diagram could be added.

Section 7.2 represents a relatively long description of the sensors, which can be significantly reduced.

Some other remarks:

Each acronym should be first defined. E.g. OGC line 68

Some phrases are not clear e.g. “An IoT standard is a middleware layer beneath one or more IoT applications that provides an application interface linked to the network through which connected nodes interact.” How is a standard a middleware? How is a set of rules a software layer?

 

In conclusion, my opinion is that the most significant part of this article, represented in sections 6,7 and 8, by the proposed architecture depicted in Figure 3 and validated in the next sections is shadowed by the excessive descriptions, which make the paper too long and relatively difficult to read.

Author Response

Please see attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript provides a comprehensive review of current IoT standards and protocols, with a particular focus on their application in precision agriculture. This thorough examination effectively positions the proposed approach within the broader context of existing research.

Real-world case studies are incorporated to demonstrate the practical implementation of the proposed architecture, adding tangible value and effectively linking theoretical concepts with practical applications.

Although the manuscript makes a noteworthy contribution to the domain of IoT systems for precision agriculture, several areas require further development prior to acceptance. Strengthening the empirical validation, addressing gaps related to security, and refining the overall structure will significantly enhance the paper’s quality.

It is recommended that the authors conduct performance assessments to benchmark the proposed architecture against alternative solutions. Key performance indicators should include data transmission efficiency, power consumption, and system reliability.

While the paper addresses interoperability to some extent, it falls short in discussing security-related issues. Considering the importance of data integrity and privacy in agricultural IoT environments, this aspect warrants a more in-depth analysis.

Overall, the paper has potential, but significant improvements are needed to meet the journal’s standards for publication.

Author Response

Please see the attached file.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

Reviewer Report

Abstract:

The abstract is concise and provides a well-structured summary of the paper, covering all essential aspects: introduction, knowledge gaps, findings, and conclusions.

Introduction:

The introduction sets the stage for the study and highlights the significance of IoT in precision agriculture. In addition, it introduces the challenges of interoperability, making the relevance of the proposed architecture clear.

Areas for Improvement:

Expand Discussion on IoT Applications:

Elaborate on existing IoT applications in agriculture, focusing on the types and volume of data collected by sensors (e.g., environmental, soil, crop, and weather data). This contextualization will better establish the importance of the proposed architecture. Highlight examples of large-scale deployments or the maximum number of sensors currently supported by existing systems.

Emphasize Challenges and Literature Gaps:

Provide a more detailed discussion of the limitations of existing interoperability solutions in IoT-based precision agriculture. For example, discuss challenges like incompatibility between devices, data silos, and the lack of scalability in current architectures. Furthermore, expand on what OGC stands for (Open Geospatial Consortium) in line 68 and briefly explain its relevance to the study for readers unfamiliar with the term.

 

Background and Paper Contribution:

The background section effectively identifies heterogeneous sensors and their roles in precision agriculture. The contributions of the paper are clearly stated and align well with the research objectives.

Areas for Improvement:

Extend the Sensor List:

In Section 2.2, include additional IoT-enabled sensors such as nitrogen, phosphorus, and potassium (NPK) sensors, as they are critical for soil analysis in precision agriculture. Discuss the importance of integrating data from these sensors into the proposed architecture to enhance its comprehensiveness and applicability.

IoT Protocols in Precision Agriculture:

The discussion of LPWAN protocols, MQTT, HTTP, and OGC SensorThings API is relevant and detailed. The modular architecture is well-justified, with practical examples demonstrating its benefits. However, the following areas can be improved:

Citations: Provide proper citations for statements in Section 3.1.1 (lines 205–207) and Section 4 (lines 373–376). This will strengthen the claims and ensure they are grounded in existing literature. Add appropriate citations for Table 6, ensuring each table cell is supported by credible sources.

Clarify Figure 4:

Modify Figure 4 to address what happens after the "Error: discard data" stage. Without this clarification, the flowchart may appear incomplete. If applicable, propose alternatives for handling errors to enhance system robustness.

Results:

Overly Technical and Dense:

While the technical depth is commendable, the section may overwhelm readers unfamiliar with the low-level details of payload parsing. Consider summarizing some of the payload analysis details (e.g., hexadecimal string breakdowns) and relegating the byte-by-byte explanations to an appendix or supplementary material.

Suggestion: Focus more on the results and implications of the payload analysis rather than the technical steps involved. Highlight the performance, scalability, or accuracy of the system in handling real-world data from IoT devices.

Lack of Quantitative Analysis:

The section does not provide metrics or performance evaluations, such as:

• • Latency in data processing.
  • Resource utilization (CPU, memory) of the connectors.
  • Reliability or error rates during data transmission.

Suggestion: Include quantitative results or performance benchmarks to demonstrate the system's efficiency and scalability. For instance, how does the proposed architecture handle large-scale deployments with multiple sensors in real agricultural scenarios?

Limited Focus on Precision Agriculture Context:

While the technical descriptions are thorough, the connection to precision agriculture could be made stronger. For example, how do these technical implementations address specific challenges in agricultural IoT systems, such as intermittent connectivity, low-power devices, or environmental conditions?

Suggestion: Provide a clearer link between the technical results and the unique demands of precision agriculture. Discuss how the system improves decision-making or operational efficiency in agricultural applications.

Figures and Listings Not Included:

Although figures and listings are referenced (e.g., Figure 6, Listing 13), their absence makes it harder to fully evaluate the results. For clarity, the narrative heavily depends on these elements.

Suggestion: Ensure that the referenced figures and code listings are included and labeled clearly. They should visually complement the text and make the explanations easier to understand.

Comparison with Existing Solutions:

The results lack a comparison with alternative approaches or existing IoT standards/protocols. This makes it difficult to assess the novelty or effectiveness of the proposed architecture.

Suggestion: Compare the proposed system with other IoT protocols (e.g., MQTT, CoAP) in terms of efficiency, interoperability, and suitability for precision agriculture. Highlight any unique advantages or improvements offered by the system.

Structure and Flow:

The section occasionally feels disjointed, with abrupt transitions between technical descriptions (e.g., SensorData vs. Libellium connectors). This can confuse readers.

Suggestion: Use subsections with consistent headings to improve organization. For example:

• • "SensorData Connector: Payload Analysis and Results."
  • "Libellium Connector: Implementation and Observations."
  • "Discussion: Implications for Precision Agriculture."

Missing Discussion of Limitations:

The section does not address the limitations of the system, such as:

• • Scalability to large networks.
  • Potential delays in entity creation during runtime.
  • Challenges in integrating heterogeneous IoT devices.

Suggestion: Acknowledge any limitations and suggest potential solutions or areas for future work.

 

Discussion:

Add Transitions Between RQs

The discussion moves abruptly between the research questions. Smooth transitions can enhance readability. For example:

Suggestion: Add a brief introductory sentence to each RQ section that connects it to the overall objectives or outcomes of the study.

Explain Technical Terms for a Broader Audience

Some terms like LPWAN, MQTT, OGC SensorThings, and FROST-Server might be unfamiliar to readers outside the field. Brief explanations or footnotes would improve accessibility.

Example:

• Replace "MQTT is generally used to connect the GWs to the internet" with "MQTT (Message Queuing Telemetry Transport), a lightweight messaging protocol, is typically used to connect the gateways (GWs) to the internet."

Balance Technical Depth with Broader Impacts

The discussion leans heavily on technical details, which is excellent for a specialized audience but may overlook broader implications or societal impacts.

Suggestion: Add a subsection emphasizing how the proposed architecture could benefit agricultural productivity, sustainability, and resource management.

Future Directions and Challenges

While the future outlook is promising, discussing potential challenges (e.g., integrating legacy systems, ensuring cybersecurity, or managing costs for smaller farms) would strengthen the discussion.

Example:

• "While the proposed architecture is scalable and cost-effective, potential challenges such as integrating legacy systems and ensuring data security must be addressed to promote adoption across diverse agricultural contexts."

Reduce Repetition

Certain concepts, such as modularity and the role of connectors, are repeated multiple times. Consolidating these discussions would improve conciseness. Example: Combine the multiple mentions of connector modularity into one comprehensive paragraph.

 

Highlight Novelty and Contributions

Explicitly emphasize what makes this work unique compared to existing solutions. For instance, how does it outperform other architectures in precision agriculture?

Suggestion:

• Add a paragraph comparing this architecture with previous works, underscoring its innovative features and practical benefits.

Clarify Future Goals for Actuators

The mention of actuators in the future outlook is promising but lacks detail. Explain how their integration could transform the system or provide specific examples of actuators (e.g., irrigation controls, fertilization systems).

Author Response

Please see attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have adressed all my concerns

Reviewer 3 Report

Comments and Suggestions for Authors

I have reviewed the changes, and I find that the revisions successfully address the concerns raised during the first review. The clarity of the methodology has improved, and the overall structure of the paper now presents a more coherent narrative. These modifications enhance the work significantly and contribute positively to its impact. I look forward to your continued progress.

Reviewer 4 Report

Comments and Suggestions for Authors

The authors properly addressed my comments and suggestions.