The remote monitoring system is growing very rapidly due to the growth of supporting technologies as well. Problem that may occur in remote monitoring such as the number of objects to be monitored and how fast, how much data to be transmitted to the data center to be processed properly. This study proposes using a cloud computing infrastructure as processing center in the remote sensing data. This study focuses on the situation for sensing on the environment condition and disaster early detection. Where those two things, it has become an important issue, especially in big cities big cities that have many residents. This study proposes to build the conceptual and also prototype model in a comprehensive manner from the remote terminal unit until development method for data retrieval. We also propose using FTR-HTTP method to guarantee the delivery from remote client to server.

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 paper proposes a stochastic hybrid dynamic model of the queue-length at a signalized intersection. The flow rate along with traffic light variables are used to define the evolution of the queue-lengths and it evolves as a piecewise linear function, being the integral of the difference between arrival and departure rate; these arrival and departure rates are described by stochastic AR model with mode-dependent parameters. The mode changes are modeled by a first order 2 or 3-state Markov process. The traffic flow rate is described using a mode-dependent first autoregressive (AR) stochastic process. The technique is applied to actual traffic flow data from the city of Jakarta, Indonesia and synthetic data from VISSIM traffic simulator. The model thus obtained via EM parameter estimation is validated by using the online particle filter. This technique can be useful and practical for periodically updating the parameters of hybrid model leading to an adaptive traffic flow state estimator as crucial part for the synthesis of traffic light control.

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Available handwashing sinks, especially during the early days of the Covid-19 pandemic, still required users to directly touch the water faucet and soap bottles. There were no guidelines for correct hand washing according to World Health Organization (WHO) standards, and water was simply wasted because the faucet was left open while scrubbing hand. Therefore, a device was developed in the form of a touchless hand-washing faucet using a sensor that can detect the presence of hands when one performing hand washing so that water only flows out when needed. The device is also equipped with a soap measuring system and indicators for soap or water containers that are full, half, or empty. To ensure that users can wash their hands properly, the device is also equipped with an announcer containing instructions for washing hands according to WHO standards. The developed device has been implemented in the field by installing it in three public places in the city of Bandung. The public can directly use this devices to fight the Covid-19 outbreak.