Energy-efficient Internet of Things monitoring with low-capacity devices

The Internet of Things (IoT) allows users to gather data from the physical environment. While sensors in public spaces are already widely used, users are reluctant to deploy sensors for shared data at their homes. The deployment of IoT nodes at the users premises presents privacy issues regarding who can access to their data once it is sent to the Cloud which the users cannot control. In this paper we present an energy-efficient and low cost solution for environmental monitoring at the users home. Our system is built completely with open source components and is easy to reproduce. We leverage the infrastructure and trust of a community network to store and control the access to the monitored data. We tested our solution during several months on different low-capacity single board computers (SBC) and it showed to be stable. Our results suggest that this solution could become a permanently running service in SBCs at the users homes.Peer ReviewedPostprint (author's final draft

Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

Implementation of an experimental platform for the social internet of things

The convergence of the Internet of Things (IoT) technologies with the social networking concepts has led to a new paradigm called the Social Internet of Things (SIoT), where the objects mimic the human behavior and create their own relationships based on the rules set by their owner. This is aimed at simplifying the complexity in handling the communications between billions of objects to the benefits of the humans. Whereas several IoT platforms are already available, the SIoT paradigm has represented only a field for pure research and simulations, until now. The aim of this paper is to present our implementation of a SIoT platform. We begin by analyzing the major IoT implementations, pointing out their common characteristics that could be re-used for our goal. We then discuss the major extensions we had to introduce on the existing platforms to introduce the functionalities of the SIoT. We also present the major functionalities of the proposed system: how to register a new social object to the platform, how the system manages the creation of new relationships, and how the devices create groups of members with similar characteristics. We conclude with the description of possible simple application scenarios

A gap analysis of Internet-of-Things platforms

We are experiencing an abundance of Internet-of-Things (IoT) middleware solutions that provide connectivity for sensors and actuators to the Internet. To gain a widespread adoption, these middleware solutions, referred to as platforms, have to meet the expectations of different players in the IoT ecosystem, including device providers, application developers, and end-users, among others. In this article, we evaluate a representative sample of these platforms, both proprietary and open-source, on the basis of their ability to meet the expectations of different IoT users. The evaluation is thus more focused on how ready and usable these platforms are for IoT ecosystem players, rather than on the peculiarities of the underlying technological layers. The evaluation is carried out as a gap analysis of the current IoT landscape with respect to (i) the support for heterogeneous sensing and actuating technologies, (ii) the data ownership and its implications for security and privacy, (iii) data processing and data sharing capabilities, (iv) the support offered to application developers, (v) the completeness of an IoT ecosystem, and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims to highlight the deficiencies of today's solutions to improve their integration to tomorrow's ecosystems. In order to strengthen the finding of our analysis, we conducted a survey among the partners of the Finnish IoT program, counting over 350 experts, to evaluate the most critical issues for the development of future IoT platforms. Based on the results of our analysis and our survey, we conclude this article with a list of recommendations for extending these IoT platforms in order to fill in the gaps.Comment: 15 pages, 4 figures, 3 tables, Accepted for publication in Computer Communications, special issue on the Internet of Things: Research challenges and solution

The Design and Development of a Multi-Disciplinary Project in Embedded Systems Design

As has been noted over the past ten years, “The wall between computer science and electrical engineering has kept the potential of embedded systems at bay. It is time to build a new scientific foundation with embedded systems design as the cornerstone, which will ensure a systematic and even-handed integration of the two fields.”[1] In Baylor University’s School of Engineering & Computer Science, the Embedded Systems course in the Department of Computer Science, and the Embedded Systems Design course in the Department of Electrical and Computer Engineering have been offered independent of each other in the recent past. In the past year, however, this is beginning to change, with plans developing to combine the project portion of the two courses into one multi-disciplinary group project. This paper will document the two courses – scope and sequence, as well as emphasis, equipment used, and delivery style – highlighting the need for a new and innovative approach at the systematic integration of software and hardware in the design and development of a mutli-disciplinary group project. The beta test of this group project is occurring in the fall 2017 semester, with full first-time full-scale deployment during the spring 2018 semester. The results of this beta test will be discussed, and the lessons learned and planned modifications to the course will be considered.Cockrell School of Engineerin

SISTEM BASIS DATA PEMANTAUAN PARAMETER AIR BERBASIS INTERNET OF THINGS (IoT) DENGAN PLATFORM THINGSPEAK

] This research aims to develop an Internet of Things (IoT)-based water parameter monitoring database system using the Thingspeak platform. This system is designed to monitor real-time water parameters such as temperature, water pH, and water turbidity. Sensors for monitoring these water parameters are installed on a Raspberry Pi microprocessor connected to the internet network. The data generated by the sensors and processed by the Raspberry Pi are then sent to the Thingspeak server. The database system developed in this research utilizes the features provided by the Thingspeak platform, such as data processing, visualization, and integration with other software. The data stored in the database can be accessed online through the dashboard provided by Thingspeak. The test results show that the IoT-based water parameter monitoring database system with the Thingspeak platform can function properly and provide accurate information on the monitored water conditions. The sensors installed on the water successfully sent data periodically to the Thingspeak platform every 10 seconds. The test results showed a deviation value of 0.9996 for the accuracy of the temperature parameter, where the accuracy value of the temperature varied from 96.30% to 100%. The average accuracy of the temperature measurement was 98.74%, and the average system error was 1.26%. The system accuracy test results range from 0.95 to 0.99. The testing was conducted on a laboratory scale, and in the future, this system can be developed for real-time water parameter monitoring over a longer period of tim

Penggunaan Internet Of Things (IoT) untuk Pemantauan dan Pengendalian Sistem Hidroponik

Internet of things (IoT) sedang marak digunakan dalam perkembangan teknologi saat ini. IoT dapat diartikan sebagai komunikasi antara satu perangkat dengan perangkat lain menggunakan internet. Kemajuan teknologi IoT ini dapat memudahkan berbagai macam pekerjaan, termasuk dalam pengendalian sistem hidroponik, sehingga perawatan tanaman dapat dilakukan dari jarak jauh dan setiap waktu. Hidroponik merupakan solusi terbaik untuk masyarakat di ibukota yang minim lahan untuk penghijauan. Komponen yang dibutuhkan dalam IoT antara lain perangkat yang mempunyai modul IoT, perangkat koneksi ke Internet seperti modem dan router, dan sebuah basis data tempat semuanya terkumpul. Tujuan dari penelitian ini adalah memanfaatkan teknologi IoT untuk memantau dan mengendalikan kondisi tanaman pada sistem hidroponik dari jarak jauh. Pengolahan hasil sensor dari mikrokontroler end device akan dikirim melalui XBee ke mikrokontroler server dan ditampilkan ke web server ThingSpeak. Sebuah aplikasi dibuat untuk smartphone yang terkoneksi dengan ThingSpeak yang dapat memantau dan mengontrol sistem kapan saja dan di mana saja. Kontrol yang dilakukan akan mengirim logika satu atau nol ke ThingSpeak dan diteruskan ke perangkat yang digunaka

Sistem Monitoring Pasien Isolasi Mandiri Covid-19 Berbasis Internet of Things

Munculnya penyakit Coronavirus Disease 2019 (COVID-19) membuat banyak yang terkena penyakit ini membuat terbatasnya fasilitas rumah sakit sebagai tempat isolasi, mulai dari yang bergejala ringan hingga tidak bergejala seperti Happy Hipoxia (pneumonia berat) membuat kadar saturasi oksigen, detak jantung, serta suhu badan akan terjadi perubahan yang abnormal, hal ini membuat pemerintah menyarankan agar yang bergejala ringan untuk isolasi mandiri. Sehingga penelitian ini membuat sistem yang dapat memonitoring pasien yang sedang  melakukan isolasi mandiri agar  beban rumah sakit  tidak semakin bertambah. Dengan menggunkan mikrokontroler ESP32 sebagai perangkat IoT (Internet of Things) data seperti SpO2  (Oxygen Saturation), heartrate, serta suhu badan sebagai paramater monitoring dapat di kirim ke server ThingSpeak. Pada penelitian ini didapatkan hasil pengukuran dari 10 subyek yang diukur. Didapatkan error pembacaan nilai SpO2  dari yang terendah 0,11% dan tertinggi 1,20%. Kemudian nilai heartrate error pembacaan terendah 0,89% dan tertinggi 1,54%. Kemudian nilai suhu badan didapatkan error pembacaan terendah 0,19% dan tertinggi 2,78%. Serta interval pengiriman data dari smartphone ke server ThingSpeak didapat sebesar <20 detik. Sehingga Sistem ini dapat digunakan dengan baik oleh pasien yang sedang malakukan isolasi mandiri karena memiliki error SpO2  yang rendah, tidak melebihi standar akurasi SpO2 sebesar ≤4%. Kata Kunci : ESP32, IoT ThingSpeak, MAX30102, DS18B20, Bluetooth