An integration between the Internet of Things (IoT) and cloud computing can potentially leverage the utilization of both sides. As the IoT based system is mostly composed by the interconnection of pervasive and constrained devices, it can take a benefit of virtually unlimited resources of cloud entity i.e storage and computation services to store and process its sensed data. On the other hand, the cloud computing system may get benefit from IoT by broadening its reach to real world environment applications. In order to incarnate this idea, a cloud software platform is needed to provide an integration layer between the IoT and cloud computing taking into account the heterogenity of network communication protocols as well as the security and data management issues. In this study, an architectural design of IoT-cloud platform for IoT and cloud computing integration is presented. The proposed software platform can be decomposed into five main components namely cloud-to-device interface, authentication, data management, and cloud-to-user interface component. In general, the cloud-to-device interface acts as a data transmission endpoint between the whole cloud platform system and its IoT devices counterpart. Before a session of data transmission established, the communication interface contact the authentication component to make sure that the corresponding IoT device is legitimate before it allowed for sending the sensor data to cloud environment. Notice that a valid IoT device can be registered to the cloud system through web console component. The received sensor data are then collected in data storage component. Any stored data can be further analyzed by data processing component. User or any developed applications can then retrieve collected data, either raw or processed data, through API data access and web console.
In IoT-based smart healthcare services, the heterogeneity of connected wearable sensing devices open up a wide opportunity to develop various healthcare services. However, it also poses an interoperability challenge since each sensing device and application may have different communication mechanisms. Considering that challenge, web platform can be seen as a promising candidate for providing an interoperability layer as we can abstract various devices as single representation i.e. web resource. In this paper, we propose the design of middleware for enabling efficient web of things access over healthcare wearable devices. The proposed middleware consists of three components: gateway-to-cloud device, messaging service and data access interface. The gateway-to-cloud device has a role to perform low level sensor data collection from various wearable sensing device through bluetooth low energy (BLE) communication protocol. Collected data are then relayed to the cloud IoT platform using a lightweight MQTT messaging protocol. In order to provide device abstraction along with access to the stored data, the system offers two kind of interfaces: the Restful HTTP identified by unique universal resource locator (URL) for batch access and MQTT websocket interface identified by unique topic to accommodate access on sensing data in near real time stream manner.
AbstrakSalah satu faktor penting yang berpengaruh terhadap kesuksesan perikanan budidaya adalah aspek kualitas air kolam yang tergambar pada beberapa parameter fisik antara lain suhu, derajat keasaman (pH), oksigen terlarut maupun kekeruhan air. Sebagai tempat hidup ikan, perubahan parameter fisik tersebut dapat berpengaruh secara langsung terhadap pertumbuhan dan daya tahan ikan budidaya. Oleh karena itu, peternak perlu melakukan pengamatan berkala terhadap kondisi air kolam budidaya untuk kemudian memberikan perlakuan tertentu agar kondisi air tetap sesuai dengan prasyarat tumbuh kembang ikan yang dibudidayakan. Peternak ikan dapat melakukan pengamatan kondisi air dengan mengambil sampel air kolam untuk kemudian diamati di laboratorium atau menggunakan peralatan sensor. Mekanisme tersebut memerlukan kehadiran peternak secara periodik pada kolam budidaya. Hal ini tentu dapat menyulitkan peternak apalagi jika ukuran kolam budidaya cukup luas. Lebih jauh lagi, kondisi fisik air dapat berubah dalam waktu yang relatif cepat, terutama karena adanya polutan baik polutan eksternal maupun internal. Pada penelitian ini dibangun sebuah sistem pemantauan kualitas air kolam budidaya ikan secara real time menggunakan jaringan sensor nirkabel. Sistem yang diusulkan terdiri atas tiga bagian, yaitu : kumpulan perangkat node sensor, perangkat gateway dan data center. Secara periodik perangkat node sensor mengukur parameter fisik air menggunakan sensor dan mengirimkannya ke perangkat gateway. Perangkat gateway kemudian mengirimkan data tersebut ke data center untuk kemudian disimpan dan diolah. Peternak dapat mengamati kondisi air kolam budidaya secara real time dari sebuah aplikasi berbasis web. Untuk melakukan validasi terhadap sistem yang dibangun, pengujian fungsionalitas dan kinerja dilakukan. Hasilnya menunjukkan bahwa sistem mampu merespons perubahan pada kondisi air seperti, tingkat kejernihan, pH, O2 terlarut dan temperatur. Sedangkan pada pengujian kinerja diperoleh hasil terbaik pada jarak 40 meter dengan besar paket 82 byte yang memberikan nilai hasil pengujian sebesar 189,4ms untuk delay dan 7,8% packetloss. AbstractThe water physical condition including water temperature, acidity level (pH) and dissolved oxygen level play an important role in the success of aquaculture. As the habitat of the fish, the changes of physical parameter in water gives a direct impact to the growth and vitality of the fish. Therefore, fish farmer needs to periodically observe that water condition and takes an immediate action upon any changes. At present, the fish farmer can perform a water monitoring by taking a water sample and observe it in laboratory. However, this method can be inefficient since the water condition can be changed rapidly due to the polutant intervention either from external or internal. Therefore, in this paper, we propose a real time aquaculture water monitoring system using wireless sensor network. The proposed system can be composed into three main components : node sensors, gateway device and data center. Periodic...
Vehicle positioning plays an important role in the design of protocols, algorithms, and applications in the intelligent transport systems. In this paper, we present a new framework of spatiotemporal local-remote sensor fusion (ST-LRSF) that cooperatively improves the accuracy of absolute vehicle positioning based on two state estimates of a vehicle in the vicinity: a local sensing estimate, measured by the on-board exteroceptive sensors, and a remote sensing estimate, received from neighbor vehicles via vehicle-to-everything communications. Given both estimates of vehicle state, the ST-LRSF scheme identifies the set of vehicles in the vicinity, determines the reference vehicle state, proposes a spatiotemporal dissimilarity metric between two reference vehicle states, and presents a greedy algorithm to compute a minimal weighted matching (MWM) between them. Given the outcome of MWM, the theoretical position uncertainty of the proposed refinement algorithm is proven to be inversely proportional to the square root of matching size. To further reduce the positioning uncertainty, we also develop an extended Kalman filter model with the refined position of ST-LRSF as one of the measurement inputs. The numerical results demonstrate that the proposed ST-LRSF framework can achieve high positioning accuracy for many different scenarios of cooperative vehicle positioning.
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