At present, many countries and regions are strengthening the construction of digital cities, expecting to obtain valuable intelligence from big data by means of information technology, and the massive accumulated security video and alarm information can be analyzed to discover the laws of the data and form correlated data to provide reference for police work. In this paper, from the actual needs of intelligence analysis, cloud computing and big data technology is used to design a cloud data(CD) intelligence investigation system(IIS) to meet the requirements of information development, by building an intelligence information center, using decision tree algorithm(DTA) to analyze and classify massive data, solve the problem of insufficient human resources for on-site investigation, effectively improve the efficiency of investigation and crime solving, and provide technical support for the construction of a harmonious and stable social environment.

Tiegang Bai. Cloud Data Intelligence Detection Based on Decision Tree Algorithm. Machine Learning Theory and Practice (2020), Vol. 1, Issue 1: 1-9. https://doi.org/10.38007/ML.2020.010101.

[1] Marziye Narangifard, Hooman Tahayori, Hamid Reza Ghaedsharaf, Mehrdad Tirandazian: Early Diagnosis of Coronary Artery Disease by SVM, Dtas and Ensemble Methods. Int. J. Medical Eng. Informatics 14(4): 295-305 (2020). 

[2] Chandrashekhar Azad, Bharat Bhushan, Rohit Sharma , Achyut Shankar, Krishna Kant Singh, Aditya Khamparia: Prediction Model Using SMOTE, Genetic Algorithm and Decision Tree (PMSGD) for Classification of Diabetes Mellitus. Multim. Syst. 28(4): 1289-1307 (2020). 

[3] Ferdinand Bollwein, Stephan Westphal: A Branch & Bound Algorithm to Determine Optimal Bivariate Splits for Oblique Decision Tree Induction. Appl. Intell. 51(10): 7552-7572 (2020). 

[4] Hsu-Che Wu, Jen-Hsiang Chen, Pei-Wen Wang: Cash Holdings Prediction Using DTAs and Comparison with Logistic Regression Model. Cybern. Syst. 52(8): 689-704 (2020). 

[5] Firoozeh Karimi, Selima Sultana, Ali Shirzadi Babakan, Shan Suthaharan: Urban Expansion Modeling Using an Enhanced DTA. Geolnformatica 25(4): 715-731 (2019). https://doi.org/10.1007/s10707-019-00377-8

[6] Muhamad Hasbullah Mohd Razali, Rizauddin Saian, Yap Bee Wah, Ku Ruhana Ku-Mahamud: An Improved ACO-Based DTA for Imbalanced Datasets. Int. J. Math. Model. Numer. Optimisation 11(4): 412-427 (2020). 

[7] Evin Sahin Sadik, Hamdi Melih Saraoglu, Sibel Canbaz Kabay, Mustafa Tosun, Cahit Keskinkilig, Gonol Akdag: Investigation of the Effect of Rosemary Odor on Mental Workload Using EEG: An Artificial Intelligence Approach. Signal Image Video Process. 16(2): 497-504 (2020). 

[8] Ekaterina Jussupow, Kai Spohrer, Armin Heinzl, Joshua Gawlitza: Augmenting Medical Diagnosis Decisions? An Investigation into Physicians Decision-Making Process with Artificial Intelligence. Inf. Syst. Res. 32(3): 713-735 (2020). https://doi.org/10.1287/isre.2020.0980

[9] Jjishnu Bhattacharyya, Manoj Kumar Dash: Investigation of Customer Churn Insights and Intelligence from Social Media: A Netnographic Research. Online Inf. Rev. 45(1): 174-206 (2020). https://doi.org/10.1108/OIR-02-2020-0048

[10] Anastasia Kioussi, Anastasios . Doulamis, Maria Karoglou, Antonia I. Moropoulou: Cultural Intelligence-Investigation of Different Systems for Heritage Sustainable Preservation. Int. J. Art Cult. Des. Technol. 9(2): 1 6-30 (2020). https://doi.org/10.4018/IJACDT.2020070102

[11] Steve Edwards: Heart Intelligence: Heuristic Phenomenological Investigation into the Coherence Experience Using Heartmath Methods. Al Soc.34(3): 677-685 (2017). https://doi.org/10.1007/s00146-017-0767-7

[12] Stefania Costantini, Giovanni De Gasperis, Raffaele Olivieri: Digital Forensics and Investigations Meet Artificial Intelligence. Ann. Math. Artif Intell.86(1-3): 193-229 (2019). https://doi.org/10.1007/s10472-019-09632-y

[13] Shahriar Akter, Katina Michael, Muhammad Rajib Uddin, Grace McCarthy, Mahfuzur Rahman: Transforming Business Using Digital Innovations: The Application of AI, Blockchain, Cloud and Data Analytics. Ann. Oper. Res.308(1): 7-39 (2020). https://doi.org/10.1007/s10479-020-03620-w

[14] Elena Verdu, Yuri Vanessa Nieto, Nasir Saleem: Call for Special Issue Papers: Cloud Computing and Big Data for Cognitive loT: Deadline for Manuscript Submission: August 15, 2020. Big Data 10(1): 83-84 (2020). 

[15] Amanpreet Kaur Sandhu: Big Data with Cloud Computing: Discussions and Challenges. Big Data Min. Anal. 5(1):32-40 (2020). 

[16] Cameron K. Peterson, David W. Casbeer, Satyanarayana G. Manyam , Steven Rasmussen: Persistent Intelligence, Surveillance, and Reconnaissance Using Multiple Autonomous Vehicles With Asynchronous Route Updates. IEEE Robotics Autom. Lett. 5(4): 5550-5557 (2020). https://doi.org/10.1109/LRA.2020.3008140

[17] Ayesha Bhimdiwala, Rebecca Colina Neri , Louis M. Gomez: Advancing the Design and Implementation of Artificial Intelligence in Education through Continuous Improvement. Int. J. Artif. Intell. Educ. 32(3): 756-782 (2020). 

[18] Irene-Angelica Chounta, Emanuele Bardone, Aet Raudsep, Margus Pedaste: Exploring Teachers’ Perceptions of Artificial Intelligence as a Tool to Support their Practice in Estonian K-12 Education. Int. J. Artif. Intell. Educ. 32(3): 725-755 (2020).