Miguel Pincheira

2.1k total citations · 2 hit papers
23 papers, 1.4k citations indexed

About

Miguel Pincheira is a scholar working on Information Systems, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Miguel Pincheira has authored 23 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Information Systems, 14 papers in Computer Networks and Communications and 4 papers in Signal Processing. Recurrent topics in Miguel Pincheira's work include Blockchain Technology Applications and Security (14 papers), IoT and Edge/Fog Computing (12 papers) and Caching and Content Delivery (5 papers). Miguel Pincheira is often cited by papers focused on Blockchain Technology Applications and Security (14 papers), IoT and Edge/Fog Computing (12 papers) and Caching and Content Delivery (5 papers). Miguel Pincheira collaborates with scholars based in Italy, Australia and Ireland. Miguel Pincheira's co-authors include Massimo Vecchio, Muhammad Salek Ali, Raffaele Giaffreda, Fabio Antonelli, Koustabh Dolui, Mubashir Husain Rehmani, Salil S. Kanhere, Elena Donini, Marco Savi and Domenico Siracusa and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Communications Surveys & Tutorials and IEEE Access.

In The Last Decade

Miguel Pincheira

19 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Applications of Blockchains in the Internet of Things: A Comprehensive Survey

2018 563 citations Muhammad Salek Ali, Massimo Vecchio et al. IEEE Communications Surveys & Tutorials profile →
Blockchain-based traceability in Agri-Food supply chain management: A practical implementation

2018 553 citations Miguel Pincheira, Muhammad Salek Ali et al. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Miguel Pincheira Italy	12	1.1k	591	260	213	131	23	1.4k
Muhammad Salek Ali Italy	7	1.1k 1.0×	627 1.1×	242 0.9×	185 0.9×	126 1.0×	7	1.3k
Raffaele Giaffreda Italy	15	796 0.8×	821 1.4×	260 1.0×	187 0.9×	122 0.9×	37	1.6k
Weili Han China	20	834 0.8×	479 0.8×	118 0.5×	367 1.7×	66 0.5×	75	1.4k
Cristian Martín Spain	11	1.3k 1.2×	1.1k 1.8×	81 0.3×	290 1.4×	157 1.2×	30	2.0k
Shih-Wei Liao Taiwan	16	627 0.6×	809 1.4×	71 0.3×	267 1.3×	99 0.8×	50	1.7k
Roberto Casado‐Vara Spain	16	496 0.5×	356 0.6×	58 0.2×	156 0.7×	117 0.9×	33	936
Ana Reyna Spain	3	1.0k 1.0×	640 1.1×	55 0.2×	172 0.8×	132 1.0×	8	1.2k
Umesh Bodkhe India	12	773 0.7×	425 0.7×	25 0.1×	221 1.0×	104 0.8×	22	1.1k
Gerard Parr United Kingdom	15	370 0.4×	687 1.2×	106 0.4×	372 1.7×	56 0.4×	133	1.6k
Junyu Wang China	16	308 0.3×	196 0.3×	257 1.0×	58 0.3×	67 0.5×	72	1.1k

Countries citing papers authored by Miguel Pincheira

Since Specialization

Citations

This map shows the geographic impact of Miguel Pincheira's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Miguel Pincheira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel Pincheira more than expected).

Fields of papers citing papers by Miguel Pincheira

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel Pincheira. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Miguel Pincheira. The network helps show where Miguel Pincheira may publish in the future.

Co-authorship network of co-authors of Miguel Pincheira

This figure shows the co-authorship network connecting the top 25 collaborators of Miguel Pincheira. A scholar is included among the top collaborators of Miguel Pincheira based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miguel Pincheira. Miguel Pincheira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Vecchio, Massimo, et al.. (2025). Toward Compliance and Transparency in Raw Material Sourcing With Blockchain and Edge AI. IEEE Access. 13. 100514–100529.

Vecchio, Massimo, et al.. (2024). Towards Cost-Effective Robotic Solution for Agricultural Data Acquisition. Iris (University of Trento). 1–6. 1 indexed citations

Pincheira, Miguel, et al.. (2024). Fostering Precision Agriculture through Affordable 3D LiDAR Deskewing with EKF. 1–6.

Antonelli, Fabio, et al.. (2024). AI-Driven Soil Moisture Forecasting for Enhanced Precision Agriculture. 221–225.

Silvestri, R., Massimo Vecchio, Miguel Pincheira, & Fabio Antonelli. (2024). Comparative Analysis of Soil Moisture Interpolation Techniques in Apple Orchards of Trentino Region. 557–562.

Pincheira, Miguel, et al.. (2023). An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments. Sensors. 23(4). 2344–2344. 44 indexed citations

Pincheira, Miguel, Elena Donini, Massimo Vecchio, & Raffaele Giaffreda. (2023). An Infrastructure Cost and Benefits Evaluation Framework for Blockchain-Based Applications. Systems. 11(4). 184–184. 2 indexed citations

Pincheira, Miguel, et al.. (2023). Overcoming Limitations of IoT Installations: Active Sensing UGV for Agricultural Digital Twins. IRIS eCampus Telematic University (Università degli Studi eCampus). 319–324. 5 indexed citations

Pincheira, Miguel, et al.. (2022). A TinyML approach to non-repudiable anomaly detection in extreme industrial environments. IRIS eCampus Telematic University (Università degli Studi eCampus). 397–402. 14 indexed citations

10.

Pincheira, Miguel, Massimo Vecchio, & Raffaele Giaffreda. (2022). Characterization and Costs of Integrating Blockchain and IoT for Agri-Food Traceability Systems. Systems. 10(3). 57–57. 11 indexed citations

11.

Pincheira, Miguel, et al.. (2022). Tiny-MLOps: a framework for orchestrating ML applications at the far edge of IoT systems. IRIS eCampus Telematic University (Università degli Studi eCampus). 1–8. 18 indexed citations

12.

Pincheira, Miguel, Elena Donini, Massimo Vecchio, & Salil S. Kanhere. (2022). A Decentralized Architecture for Trusted Dataset Sharing Using Smart Contracts and Distributed Storage. Sensors. 22(23). 9118–9118. 18 indexed citations

13.

Pincheira, Miguel, Elena Donini, Raffaele Giaffreda, & Massimo Vecchio. (2020). A Blockchain-Based Approach To Enable Remote Sensing Trusted Data. IRIS eCampus Telematic University (Università degli Studi eCampus). 652–657. 17 indexed citations

14.

Pincheira, Miguel, Massimo Vecchio, & Raffaele Giaffreda. (2020). Rationale and Practical Assessment of a Fully Distributed Blockchain-based Marketplace of Fog/Edge Computing Resources. IRIS eCampus Telematic University (Università degli Studi eCampus). 165–170. 4 indexed citations

15.

Pincheira, Miguel, Massimo Vecchio, Raffaele Giaffreda, & Salil S. Kanhere. (2020). Exploiting constrained IoT devices in a trustless blockchain-based water management system. IRIS eCampus Telematic University (Università degli Studi eCampus). 1–7. 23 indexed citations

16.

Savi, Marco, et al.. (2020). A Blockchain-based Brokerage Platform for Fog Computing Resource Federation. BOA (University of Milano-Bicocca). 147–149. 12 indexed citations

17.

Pincheira, Miguel, Massimo Vecchio, Raffaele Giaffreda, & Salil S. Kanhere. (2020). Cost-effective IoT devices as trustworthy data sources for a blockchain-based water management system in precision agriculture. Computers and Electronics in Agriculture. 180. 105889–105889. 80 indexed citations

18.

Pincheira, Miguel, Elena Donini, Raffaele Giaffreda, & Massimo Vecchio. (2020). A BLOCKCHAIN-BASED APPROACH TO ENABLE REMOTE SENSING TRUSTED DATA. SHILAP Revista de lepidopterología. IV-3/W2-2020. 35–40. 4 indexed citations

19.

Ali, Muhammad Salek, Massimo Vecchio, Miguel Pincheira, et al.. (2018). Applications of Blockchains in the Internet of Things: A Comprehensive Survey. IEEE Communications Surveys & Tutorials. 21(2). 1676–1717. 563 indexed citations breakdown →

20.

Pincheira, Miguel, Muhammad Salek Ali, Massimo Vecchio, & Raffaele Giaffreda. (2018). Blockchain-based traceability in Agri-Food supply chain management: A practical implementation. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1–4. 553 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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