No abstract

Pada sektor transportasi dan stasiun pemantau cuaca, GPS (Global Positioning System) memegang peranan penting dalam perkembangannya. GPS seringkali mengalami kendala hilangnya sinyal atau gangguan luar lainnya, seperti cuaca buruk atau sinyal GPS yang tertahan pada lapisan atmosfer. Oleh karena itu, diperlukan suatu perangkat lain atau sensor untuk mendukung kinerja GPS. Dengan adanya sensor gyroscope dan accelerometer diharapkan dapat memperbaiki kinerja GPS dan dapat menggantikan GPS sementara apabila GPS mengalami gangguan. Pemodelan dan perancangan sebuah sensor fusion diperlukan untuk membantu kinerja dan meningkatkan akurasi GPS dalam membaca suatu posisi dan kecepatan. Implementasi sensor fusion tersebut akan memudahkan para pengguna GPS, terutama untuk navigasi agar lokasi dan kecepatan yang didapatkan lebih akurat

This Research presents a macroscopic model of traffic flow as the basis for making Intelligent Transportation System (ITS). The data used for modeling is The number of passing vehicles per three minutes. The traffic flow model created in The form of Fluid Flow Model (FFM). The parameters in The model are obtained by mixture Gaussian distribution approach. The distribution consists of two Gaussian distributions, each representing the mode of traffic flow. In The distribution, intermode shifting process is illustrated by the first-order Markov chain process. The parameters values are estimated using The Expectation-maximization (EM) algorithm. After The required parameter values are obtained, traffic flow is estimated using the Observation and transition-basedmost likely estimates Tracking Particle Filter (OTPF). To Examine the accuracy of the model has been made, the model estimation results are compared with the actual traffic flow data. Traffic flow data is collected on Monday 20 September 2017 at 06.00 to 10.00 on DipatiukurRoad, Bandung. The proposed model has accuracy with MAPE value below 10%, or falls into highly accurate categories

Efforts to integrate sensor networks into internet have been widely pursued. A FTR-HTTP (Finite Time Response Hyper Text Transfer Protocol)has beenproposed to integrate the sensor networks witha data collector server through internet. The FTR-HTTP has two controlvariables, i.e. forced sleep duration (K) and maximum response time (MaxTr),in which both affect the performance of the FTR-HTTP. This paper reports some experimental researches that demonstratethe effects of variations of the two control variables on the performance of the FTR-HTTP. The results show that increasing the value of Kvariable has an effect on the improvements of three performance measures of FTR-HTTP, i.e. average response time, average energyefficiency, and average request timeout. Where as, increasing the value of Kvariable can increase the value of average update time, which can be described as a sampling frequency of data transmission to the server. It means that increasing the value of Kvariable can improve thethree performance measures (average response time, average energy efficiency, and average request timeout), but trade off must be made in the expense of averageupdate time. The results of the experiment show that increasing the value of Max TR variable has little positive effect on three performance measures of the FTR-HTTP (average response time, energy efficiency, and average update), but it has little negative effects on the other performance measure of the FTR-HTTP (average request timeout). Finally, a closed-loop control system being able to achieve the optimal performance of the FTR-HTTP, by controlling the value of K and Max TR variables, can be proposed for futureworks.