Abstract - Cardiovascular disease (coronary heart, high blood pressure, cardiac arrhythmia, and other cardio/vascular problems) is one of the main death cause in the world. In developing country like Indonesia, the situation is worse due to lack of physicians to serve the patients. Based on these facts, we need new innovations to improve the life expectancy of cardiovascular disease patients, with help of machine-to-machine (M2M) technology. This research aims to develop a health monitoring system (healthcare) and medication recommendation (health-cure) for cardiovascular patients who stay at home. Patient’s vital signs (heart rate, blood pressure, and heart rhythm) will be monitored through sensors, which will report to M2M server. Then the server will give medication recommendation automatically using one of artificial intelligence (AI) technique called Case- Based Reasoning, based on several medical records from hospitals and other references. Physician/hospital will be involved as supervisor/advisor in this project since we deal with serious disease which may threaten patient’s life. I. INTRODUCTION These days cardiovascular disease, i.e. problems in heart and vasculars (coronary heart, high blood pressure, cardiac arrhythmia, and other cardio/vascular problems) [1 ] is one of the main death cause in the world. Based on a research [2 ], cardiovascular disease is 48% of death cause in Europe. Meanwhile, in developing country like Indonesia, the situation is worse due to lack of physicians to serve the residents (36 doctors per 100,000 population) [3 ]. Based on these facts, we need new innovations in order to improve the life expectancy of cardiovascular disease patients, with help of technology. This study aims to propose a help for cardiovascular disease patients who stay at home, by monitoring and giving automatic recommendations for medication, using one of artificial intelligence (AI) technique called Case-Based Reasoning (CBR). In the end, physician/hospital should be involved in this project since we deal with serious disease which may threaten patient’s life. The rest of this paper is organized as follows. Section 2 discusses about literature review while section 3 is the methodology: architectural design and artificial intelligence. Section 4 discusses about the implementation and Section explains the results expected. Then last we will conclude this topic in Section 6. II. LITERATURE REVIEW The advancement of technology enables electronic equipments to communicate each other without human intervention which we call machine-to-machine (M2M) technology [4 ]. Some researches of M2M have been done in healthcare field, some to help in patient vital signs monitoring [5-9 ] by attaching some sensors around patient’s body and automatically report to M2M server. One of them is “WeHealth” which proposed an integrated medical service in China to monitor patients who suffer chronic disease e.g. hypertension [10 ]. Another research is a portable body area network (BAN) clinic which was designed to implement a remote clinic in an urban region in Bangladesh [11 ]. Most of existing M2M researches in medical field's scope are in healthcare, and few of them talk about health-cure or medication like we do in this research. Meanwhile, AI and other expert systems have been used in many researches about healthcare and medication. For example, [12] used data mining techniques i.e. Decision Trees, Naive Bayes, and Neural Network to predict heart disease for patients with certain at attributes. Chaurasia et al did the similar topic but with different techniques: CART, ID3, and decision table [13]. Other research has been done by Lopez and Plaza which explains about case-based learning to be used in medical diagnosis [14]. In this research we will use CBR technique and Nearest Neighbor algorithm to diagnose and give medication recommendation, since the techniques are quite simple and efficient according to [15], and CBR actually is a way of thinking of how doctors treat their patients, they give diagnosis based on their experience in treating previous cases, besides their medical knowledge as well. III. METHODOLOGY A. Architectural Design The big picture of this research is depicted in Figure 1. First, the system should monitor patient’s vital signs (heart rate, blood pressure, and heart rhythm) then periodically reports it to M2M server via Internet cloud. M2M server will collect the data and analyze them. The result will be a medication recommendation for the patient based on the actual data and the Designing Machine-to-Machine (M2M) System In Health-Cure Modeling For Cardiovascular Disease Patients: Initial Study I Ketut Agung Enriko 1 , Gunawan Wibisono 2 , Dadang Gunawan 3 Department of Electrical Enginering Universitas Indonesia Email: 1 i.ketut42@ui.ac.id , 2 gunawan@eng.ui.ac.id , 3 guna@eng.ui.ac.id