Aisha Siddiqa

10 papers receiving 1.1k citations

Aisha Siddiqa's Hit Papers

Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges 2017 · 594 citations
5940+3+6Years since publication100200300400500

Peers

Aisha Siddiqa
Comparison fields: 5 of 110
  • Computer Networks and Communications 520
  • Management Information Systems 193
  • Information Systems 362
  • Information Systems and Management 81
  • Signal Processing 124
Replace Mohsen Marjani with:
Mohsen Marjani Malaysia
Fariza Hanum Nasaruddin Malaysia
Sunil Kumar Khatri India
Kerry Taylor Australia
Ernesto Expósito France
Pankesh Patel India
Abdelmuttlib Ibrahim Abdalla Ahmed Malaysia
Haoyong Lan United States
Ahmad Karim Pakistan
Chi Yang Australia
Aisha Siddiqa relative to Mohsen Marjani Malaysia Mohsen Marjani's profile →
Citations per field
00.5×3.8×
Mohsen Marjani · 1×
Citations per year

Countries citing papers authored by Aisha Siddiqa

Since Specialization
Citations

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

Fields of papers citing papers by Aisha Siddiqa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Aisha Siddiqa, 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 Aisha Siddiqa Line = papers co-authored together Aisha Siddiqa links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges
Hit paper breakdown →
2017594
2 2015182
3 2016154
4 201777
5 201755
6 201727
7 201619
8 202413
9 20175
10 20175
11 20250

About Aisha Siddiqa

Aisha Siddiqa is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Management Information Systems, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (5 papers), Cloud Computing and Resource Management (5 papers), Data Management and Algorithms (3 papers), Caching and Content Delivery (3 papers), Big Data and Business Intelligence (2 papers), Green IT and Sustainability (1 paper), Advanced Database Systems and Queries (1 paper) and Context-Aware Activity Recognition Systems (1 paper). The work is most often cited by research in Computer Networks and Communications (520 citations), Management Information Systems (193 citations), Information Systems (362 citations), Information Systems and Management (81 citations) and Signal Processing (124 citations). Aisha Siddiqa has collaborated with scholars based in Malaysia, Pakistan and China. Frequent co-authors include Abdullah Gani, Fariza Hanum Nasaruddin, Ahmad Karim, Mohamed Hashem, Ibrar Yaqoob, Mohsen Marjani, Shahaboddin Shamshirband, Victor Chang, Samee U. Khan and Junaid Shuja. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, Future Generation Computer Systems, Neural Computing and Applications, IEEE Access and Knowledge and Information Systems.

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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