Implementasi Protokol CoAP pada Smart Building Berbasis OpenMTC

Pada tugas akhir ini, dilakukan penelitian mengenai komunikasi pada smart building, dengan mengaplikasikan protokol CoAP dalam platform middleware M2M OpenMTC yang sebelumnya memiliki protokol standar, yaitu HTTP. Protokol CoAP berperan dalam komunikasi antara sensor atau device application dan GSCL OpenMTC. Pengujian kinerja dilakukan dengan pengiriman data sensor sebesar 10, 100, dan 1000 dan ditentukan dengan parameter analisis delay, throughput, dan overhead protokol. jumlah tersebut dinilai mewakili banyaknya data sensor pada suatu bangunan. Hasil dari pengujian dan analisis menunjukan bahwa protokol CoAP memiliki delay yang lebih rendah, throughput yang lebih stabil ketika data sensor menuju 1000, serta protokol CoAP memiliki overhead sekitar 50% lebih rendah dibandingkan dengan protokol HTTP. Kata kunci : CoAP, OpenMTC, HTTP, Smart building, Kinerja

Increasing Smoke Classifier Accuracy using Naïve Bayes Method on Internet of Things

This paper proposes fire alarm system by implementing Naïve Bayes Method for increasing smoke classifier accuracy on Internet of Things (IoT) environment. Fire disasters in the building of houses are a serious threat to the occupants of the house that have a hazard to the safety factor as well as causing material and non-material damages. In an effort to prevent the occurrence of fire disaster, fire alarm system that can serve as an early warning system are required. In this paper, fire alarm system that implementing Naïve Bayes classification has been impelemented. Naïve Bayes classification method is chosen because it has the modeling and good accuracy results in data training set. The system works by using sensor data that is processed and analyzed by applying Naïve Bayes classification to generate prediction value of fire threat level along with smoke source. The smoke source was divided into five types of smoke intended for the classification process. Some experiments have been done for concept proving. The results show the use of Naïve Bayes classification method on classification process has an accuracy rate range of 88% to 91%. This result could be acceptable for classification accuracy

Medical application of the Internet of Things (IoT): prototyping a telemonitoring system

The Internet of Things (IoT) is a technological paradigm that can be perceived as an evolution of the internet. It is a shift from the traditional way of connecting devices to the internet, both in number and diversity of connected devices. This significant and marked growth in the number and diversity of devices connected to the internet has prompted a rethink of approaches to interconnect devices. The growth in the number of connected devices is driven by emerging applications and business models and supported by falling device costs while the growth in the diversity is driven by the reduction in the cost of manufacturing these devices. This has led to an increase in the number of users (not limited to people) of the internet. According to statistics by the ITU, by the end of 2015, about 3.2 billion people were using the Internet. Significantly, 34% of households in developing countries had Internet access, with more than 80% of households in developed countries. This indicates that it is realistic to leverage the IoT in living spaces. Appreciating this potential, many sectors of society are already positioning themselves to reap the benefits of this great promise. Hence the health sector would do well to adopt this technological paradigm to enhance service delivery. One specific area where the health sector can benefit from the adoption of the IoT is in telemonitoring and the associated early response to medical emergencies. Statistics and research show that there are areas in the medical field, that still need improvement to enhance service delivery. The Nursing Times has summed up these areas into four categories. The first one is a need to have a regular observation of patients and their vital signs. Here, health service providers (SPs) need to adopt creative and non-obtrusive methods that will encourage patients' participation in the monitoring of these vital signs. As much as possible, vital signs readings should be taken at convenient locations and times. Therefore, devices that have consistent internet access and are usually a part of daily life for most patients, such as the mobile phones would prove to be a key enabler of regular observation of vital signs. Furthermore, miniaturization of the vital signs monitoring or sensing devices would be a key step towards realizing this scenario. A lot of work is already being done to miniaturize these devices and make them as much a part of daily life as possible, as evidenced by advancements in the field of fitness and wearables. To map this use to the medical field, a system needs to be created that would allow for the aggregation of these disparate measuring and monitoring devices with medical information management systems. The second potential area of improvement is in the early recognition of deterioration of the patients. With regular observation of patients, it is possible to recognize deterioration at its early stage. Taking cognizance of the different needs of the various stakeholders is important to achieve the intended results. The third potential area of improvement is in the communication among stakeholders. This has to do with identifying the relevant data that must be delivered to the stakeholders during the monitoring and management process. Lastly, effective response to medical concerns is the other potential area of improvement. It is noted that patients do not generally get the right response at the right time because the information does not reach the rightly qualified personnel in good time. The regular and real-time capture of vital signs data coupled with added analytics can enable IoT SPs to design solutions that automate the management and transmission of medical data in a timely manner. This work addresses how the medical sector can adopt IoT-based solutions to improve service delivery, while utilizing existing resources such as smartphones, for the transmission and management of vital signs data, availing it to stakeholders and improve communication among them. It develops a telemonitoring system based on IoT design approaches. The developed system captures readings of vital signs from monitoring devices, processes and manages this data to serve the needs of the various stakeholders. Additionally, intelligence was added to enable the system to interpret the data and make decisions that will help medical practitioners and other stakeholders (patients, caregivers, etc.) to more timely, consistently and reliably provide and receive medical services/assistance. Two end user applications were developed. A cloud-based web application developed using PHP, HTML, and JavaScript and an Android mobile application developed using Java programming language in Android studio. An ETSI standards-compliant M2M middleware is used to aggregate the system using M2M applications developed in Python. This is to leverage the benefits of the standards-compliant middleware while offering flexibility in the design of applications. The developed system was evaluated to assess whether it meets the requirements and expectations of the various stakeholders. Finally, the performance of the proposed telemonitoring system was studied by analyzing the delay on the delivery of messages (local notifications, SMS, and email) to various stakeholders to assess the contribution towards reducing the overall time of the cardiac arrest chain of survival. The results obtained showed a marked improvement (over 28 seconds) on previous work. In addition to improved performance in monitoring and management of vital signs, telemonitoring systems have a potential of decongesting health institutions and saving time for all the stakeholders while bridging most of the gaps discussed above. The captured data can also provide the health researchers and physicians with most of the prerequisite data to effectively execute predictive health thereby improving service delivery in the health sector

Software for Simplifying Embedded System Design Based on Event-Driven Method

Complexity of embedded system application increases along with the escalation of market demand. Embedded system design process must be enhanced to face design complexity problem. One of challenges in designing embedded system is speed, accuracy, and flexibility. The design process is usually conducted recursively to fulfill requirement of user and optimization. To solve this problem, it needs a system design that is flexible for adaptation. One of solutions is by optimizing all or some of the design steps. This paper proposes a design framework with an automatic framework code generator with of event driven approach. This software is a part of a design flow which is flexible and fast. Tron game and simple calculator are presented as a case study. Test result shows that this framework generator can increase speed of design’s flexibility

Egg Quality Detection System Using Fuzzy Logic Method

Determining the quality of eggs in general is used by placing eggs on a flashlight. The detection system is very necessary to determine good egg quality or rotten eggs, so that the conditions of the eggs can be known by the chicken farm company and then will be sold to the community. This egg detecting system utilizes several sensor devices that are combined. The sensor used to detect the quality of eggs is a light sensor and a heavy sensor by connected with a microcontroller. So that there is no ambiguity towards the decision making of good egg or rotten eggs, then processing the data is obtained from these sensors using Fuzzy Logic and Firebase methods in real time as data storage media, and actuators will distribute or separate good eggs or the rotten eggs one. With the development of technology now, we can use the Internet of Things (IoT) technology, one of the systems check the quality of eggs which are good or not good. This system is built using a microcontroller to coordinate the running of the system using the Fuzzy Logic Method that applies inside. Final information is obtained on the form of egg quality in real time. The test results were carried out using the Fuzzy Logic method and obtained 95% results from 20 eggs and had 1 wrong egg. When using system hardware without using the fuzzy logic method on the microcontroller that using only a light sensor and a heavy sensor it produces a result of 75% from 20 eggs and had 5 wrong eggs. Using the egg detection optimization method can be increased up to 20%

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Infraestrutura segura e descentralizada para a internet das coisas

Mestrado em Engenharia Eletrónica e TelecomunicaçõesDespite many IoT Infrastructures having been implemented in recent years, none of them is truly prepared for a global deployment, where failure tolerance and scalability are an essential requirement. This dissertation presents an alternative concept for IoT Infrastructures, which focuses on enhancing the traditional centralized architecture, usually operated by a single entity, into a decentralized architecture featuring multiple entities and use cases. We propose a dynamic, community driven and self-configurable infrastructure on top of a structured Peer-to-Peer network, based on a Distributed Hash Table. Moreover, the proposed infrastructure is flexible enough to allow each peer of the overlay to enable a set of different services, according to its capabilities. In addition, a set of communication protocols is provided in order to support heterogeneous devices, as well as data access, streaming and persistence. It is also an important focus of our proposal to have mechanisms that guarantee the privacy and security of the information flow and storage.Apesar de várias infraestruturas para IoT terem sido implementadas nos últimos anos, nenhuma delas está realmente preparada para ser utilizada a uma escala global, onde a escalabilidade e a tolerância a falhas são um requisito essencial. Esta dissertação apresenta um conceito alternativo de infraestruturas para a IoT, cujo foco consiste em evoluir a tradicional arquitetura centralizada, normalmente utilizada por uma entidade única, para uma arquitetura descentralizada, compatível com múltiplas entidades e casos de uso. Propomos uma infraestrutura auto-configurável, dinâmica e orientada à comunidade, construída em cima de uma rede Peer-to-Peer estruturada, baseada numa Distributed Hash Table. Além disso, a infraestrutura proposta é suficientemente flexível para permitir que cada peer da rede possa ativar diferentes serviços, mediante as suas capacidades. Por outro lado, um conjunto de protocolos de comunicação é providenciado, de modo a suportar dispositivos heterogéneos, bem como o acesso aos dados e a sua transmissão e persistência. Também é um foco importante desta proposta a disponibilização de mecanismos que garantam a privacidade e segurança da informação durante a sua transmissão e o seu armazenamento