Javier Prieto

99 papers receiving 2.1k citations

Hit Papers

An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario 2019 · 206 citations
2060+2+5Years since publication50100150200250

Peers

Javier Prieto
Comparison fields: 5 of 152
  • Information Systems 570
  • Computer Networks and Communications 553
  • Statistics and Probability 154
  • Computer Science Applications 79
  • Management Information Systems 129
Replace Debashis De with:
Debashis De India
Victoria López Spain
Shohei Shimizu Japan
Thomas A. Runkler Germany
Qing Liu China
Junhao Wen China
Isaac Triguero Spain
Jing He China
Tarıq Samad United States
Theodora Varvarigou Greece
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Citations per year

Countries citing papers authored by Javier Prieto

Since Specialization
Citations

This map shows the geographic impact of Javier Prieto'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 Javier Prieto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier Prieto more than expected).

Fields of papers citing papers by Javier Prieto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Javier Prieto. 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 Javier Prieto. The network helps show where Javier Prieto may publish in the future.

Co-authors

The 25 scholars most cited alongside Javier Prieto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Javier Prieto Line = papers co-authored together Javier Prieto links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1
How blockchain improves the supply chain: case study alimentary supply chain
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2018275
2 1999246
3
An intelligent Edge-IoT platform for monitoring livestock and crops in a dairy farming scenario
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2019206
4 201288
5 202075
6 201870
7 201864
8 201961
9 201648
10 201947
11 201040
12 201739
13 201037
14 201834
15 201933
16 201932
17 201630
18 202029
19 201827
20 201826

About Javier Prieto

Javier Prieto is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Information Systems and Ocean Engineering, having authored 103 papers that have together received 2.2k indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (22 papers), IoT and Edge/Fog Computing (13 papers), Blockchain Technology Applications and Security (13 papers), Underwater Vehicles and Communication Systems (13 papers), Target Tracking and Data Fusion in Sensor Networks (9 papers), Smart Grid Energy Management (9 papers), Speech and Audio Processing (8 papers) and Anomaly Detection Techniques and Applications (7 papers). The work is most often cited by research in Information Systems (570 citations), Computer Networks and Communications (553 citations), Statistics and Probability (154 citations), Computer Science Applications (79 citations) and Management Information Systems (129 citations). Javier Prieto has collaborated with scholars based in Spain, Japan and United States. Frequent co-authors include Juan M. Corchado, Roberto Casado‐Vara, Fernando De la Prieta, Ricardo S. Alonso, Alfonso González‐Briones, Óscar García, Alfonso Bahillo, Santiago Mazuelas, Sara Rodrı́guez and Inés Sittón-Candanedo. Their work appears in journals such as Sensors, Energies, IEEE Access, Neurocomputing and Sustainability.

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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