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Abstrak :
Denecke’s objective is to introduce the multiple possibilities and facets of surveillance and its applications. She first introduces the task of surveillance and provides an overview on surveillance in various domains. Next, the various information sources that are available and could already be used by surveillance systems are summarized. In the main part of the book, her focus is on unstructured data as a source for surveillance. An overview on existing methods as well as methods to be developed in order to process this kind of data with respect to surveillance is presented. As an example application, she introduces disease surveillance using Web 2.0, including corresponding methods and challenges to be addressed. The book closes with remarks on new possibilities for surveillance gained by recent developments of the Internet and mobile communication, and with an outline of future challenges.

Abstrak :
This concise textbook/reference examines the fundamental aspects of intelligent computing for surveillance systems, from camera calibration and data capturing, to secure data transmission. The text covers digital surveillance from the level of an individual object or biometric feature, to the full lifecycle of an event. This is followed by a detailed discussion on how an intelligent system can independently monitor and learn from an event, and invite human input when necessary. The book concludes with a presentation on how the computation speed of the system can be enhanced through the use of supercomputing technology.

Abstrak :
Diabetes mellitus tipe 2 telah menjadi masalah kesehatan masyarakat yang serius dan merupakan penyebab penting dari angka kesakitan, kematian, kecacatan dan kerugian ekonomi di seluruh dunia termasuk Indonesia. Provinsi DKI Jakarta termasuk sepuluh besar penyakit diabetes mellitus tertinggi secara nasional. Posbindu PTM sebagai salah satu program pemerintah dalam melakukan kegiatan deteksi dini dan pemantauan faktor risiko PTM yang dilaksanakan secara terpadu, rutin, dan periodik. Penelitian ini bertujuan untuk mengetahui faktor risiko yang berhubungan dengan diabetes mellitus tipe 2 di Posbindu PTM se-Provinsi DKI Jakarta. Penelitian ini menggunakan desain cross sectional dari data Surveilans Faktor Risiko PTM Dinas Kesehatan Provinsi DKI Jakarta tahun 2017. Sampel yang dianalisis sebesar 12.775 responden dari 12.789 responden berumur ge;15 tahun. Analisis data multivariat menggunakan uji regresi logistik berganda untuk menentukan model prediksi dan faktor potensial dampak yang paling dominan. Hasil didapatkan proporsi diabetes mellitus sebesar 15,87. Multivariat didapatkan umur ge;45 tahun POR=6,32, 35-44 tahun POR=1,82, 25-34 tahun POR=0,98, jenis kelamin POR=0,63, riwayat DM keluarga POR=4,43, tidak menikah POR=0,49, cerai POR=1,58, tidak bekerja POR=1,93, IRT POR=1,84, pelajar/mahasiswa POR=0,24, kurang aktif POR=1,20, hipertensi POR=1,35, dan obesitas sentral POR=1,29. Faktor risiko yang memberikan dampak paling dominan adalah umur ge;45 tahun dan riwayat DM keluarga, sedangkan faktor yang dapat dimodifikasi yang memberikan dampak paling dominan adalah obesitas sentral. Model prediksi ini cukup akurat untuk memprediksi diabetes mellitus dengan batas probabilitas sebesar 18. Perlu adanya peningkatan kualitas pelaksanaan Posbindu PTM dari pemerintah serta kesadaran warga DKI Jakarta yang berumur ge;15 tahun untuk pemantauan faktor risiko serta deteksi dini PTM. ......Type 2 diabetes mellitus has become a serious public health problem and is an important cause of morbidity, death, disability and economic losses worldwide including Indonesia. The province of DKI Jakarta includes the top ten of the highest diabetes mellitus nationally. Posbindu PTM as one of the government programs in conducting early detection and monitoring of NCD risk factors that are implemented in an integrated, routine, and periodic. This study aims to determine the risk factors associated with diabetes mellitus type 2 in Posbindu PTM throughout DKI Jakarta Province. This research uses cross sectional design from data of Risk Factor Surveilans of NCD Health Office of DKI Jakarta Province 2017. The analyzed sample is 12,775 respondents from 12,789 respondents aged ge 15 years old. Multivariate data analysis using multiple logistic regression test to determine prediction model and the most dominant potential impact factor. The result obtained proportion of diabetes mellitus equal to 15,87. Multivariate was found to be ge 45 years old POR 6.32, 35 44 years POR 1.82, 25 34 years POR 0.98, sex POR 0.63, history of DM family POR 4.43, unmarried POR 0.49, divorce POR 1.58, not working POR 1.93, IRT POR 1.84, student POR 0.24, less physical activity POR 1.20, hypertension POR 1.35, and central obesity POR 1.29. Risk factors that have the most dominant impact are age ge 45 years and family DM history, while the modifiable factor that gives the most dominant impact is central obesity. This prediction model is accurate enough to predict diabetes mellitus with a probability limit of 18. It is necessary to improve the quality of Posbindu PTM implementation from the government and the awareness of Jakarta citizens aged ge 15 years for monitoring of risk factors and early detection of NCD.