Muhammad Imran

24.4k citations
366 papers · 16.7k indexed · 17 hit papers · h-index 65

Muhammad Imran

355 papers receiving 16.0k citations

Hit Papers

A smart healthcare monitoring system for heart disea...5262016202620192022200400600

Peers

Muhammad Imran
Comparison fields: 5 of 190
  • Computer Networks and Communications 7.8k
  • Information Systems 4.1k
  • Industrial and Manufacturing Engineering 1.2k
  • Artificial Intelligence 3.7k
  • Signal Processing 1.2k
Replace Giancarlo Fortino with:
Giancarlo Fortino Italy
Thippa Reddy Gadekallu India
Arun Kumar Sangaiah India
Zhihan Lv China
Joel J. P. C. Rodrigues Portugal
Mohammad Mehedi Hassan Saudi Arabia
M. Shamim Hossain Saudi Arabia
Sudeep Tanwar India
Gautam Srivastava Canada
Laurence T. Yang Canada
Muhammad Imran relative to Giancarlo Fortino Italy Giancarlo Fortino's profile →
Citations per field
00.5×1.5×2.1×
Giancarlo Fortino · 1×
Citations per year

Countries citing papers authored by Muhammad Imran

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Imran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Muhammad Imran, 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 Muhammad Imran Line = papers co-authored together Muhammad Imran links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20253
3 20247
4 202417
5 20244
6 20247
7 20236
8 202339
9 202313
10 202239
11 202120
12 202116
13 202116
14 20201
15 202044
16 201964
17
The role of big data analytics in industrial Internet of Thingsbreakdown →
2019255
18 201921
19
Real-time big data processing for anomaly detection: A Surveybreakdown →
2018317
20
Fuzzy Logic Based Flow Controller of Dam Gates
20163

About Muhammad Imran

Muhammad Imran is a scholar working on Computer Networks and Communications, Information Systems and Signal Processing, having authored 366 papers that have together received 16.7k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (75 papers), Energy Efficient Wireless Sensor Networks (62 papers), Energy Harvesting in Wireless Networks (38 papers), Blockchain Technology Applications and Security (33 papers), Network Security and Intrusion Detection (32 papers), Vehicular Ad Hoc Networks (VANETs) (28 papers), Underwater Vehicles and Communication Systems (26 papers) and Wireless Body Area Networks (26 papers). The work is most often cited by research in Computer Networks and Communications (7.8k citations), Information Systems (4.1k citations) and Industrial and Manufacturing Engineering (1.2k citations). Muhammad Imran has collaborated with scholars based in Saudi Arabia, Pakistan and Australia. Frequent co-authors include Ibrar Yaqoob, Ejaz Ahmed, Imran Razzak, Jiafu Wan, Abdullah Gani, Hong‐Ning Dai, Muhammad Shoaib, Athanasios V. Vasilakos, Di Li and Mohsen Guizani. Their work appears in journals such as IEEE Access, Future Generation Computer Systems, IEEE Communications Magazine, Sensors and Computer Communications.

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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