Implementation aspects and offline digital signal processing of a smart pebble for river bed sediment transport monitoring

Conceptualization aspects of a smart sediment particle (smart pebble) for monitoring of sediment transport in riverbeds have been documented previously [1]. However, this mixed signal approach was done only at a conceptual level and lacks complete implementation aspects such as limited PCB real estate, a miniaturized power source and adequately addressing the offset errors. A fully digital version with multiple strap-down MEMs, signal conditioning blocks, an 8-bit processor and a memory subsystem was designed and assembled within a less than 4 cm diameter sphere to allow data capture for up to 15 minutes. This compact subsystem allows exporting of output data, stored within the memory from nine sampled MEM sensors, into an offline-processing environment for further processing to generate essential motion information. Complex mathematical algorithms for axis conversion, etc, are housed within the offline-processing environment reducing the burden on the smart pebble. The total electronic subsystem embedded within the pebble together with the external processing algorithms tackle cumulative errors, gravitational compensation requirements and offset errors, while being powered by a specially designed power stage, based on a single alkaline cell

Vulnerabilities in IoT devices for smart home environment

Recently, consumers have seen multiple products being advertised as smart home. These products promise to make our homes more comfortable, safe, automated, and remotely controlled. To this new reality of processing information it was given the name IoT (Internet of Things). Many news headlines have been published exposing serious security vulnerabilities in many IoT devices, with some of them being exploited to make one of the largest DDoS attacks recorded. In this paper we present a method developed with the purpose of identifying high risk vulnerabilities in smart home IoT devices, giving application examples of actual vulnerabilities found in two commercially available devices. This method uses several open source tools to identify vulnerabilities in some of these IoT devices. Besides, we will also present some topics related to the main threats and vulnerabilities that affect smart home IoT devices.publishersversionpublishe

INTELLIGENT AND ADAPTIVE FUZZY CONTROL SYSTEM FOR ENERGY EFFICIENT HOMES

“Smart houses” have widely established their position as a research field during the last decade. Nowadays the technical solutions related to energy resource management are being rapidly developed and integrated into the daily lives of people. The energy resource management systems use sensor networks for receiving and processing information during the realia time. Smart house adaptive and intelligent solutions has advanced towards common environment, which can take care of the inhabitants’ well-being in numerous ways. This paper propose to use a context sensitive and proactive fuzzy control system for controlling the automation processes in smart house environment. The designed monitoring system has adaptive and intelligent options, and it can operate using real time information received from sensors. The system is designed to operate fully in the background and can be installed to any exiting working system. This paper describes a central heating boiler control system implemented using the fuzzy control system designed. Author concentrates on the basic operation of such systems and present findings from the design process and initial tests

Mapping the NGSI-LD Context Model on Top of a SPARQL Event Processing Architecture: Implementation Guidelines

NGSI-LD is an open specification released by ETSI which proposes an information model and an API for an easy to use and standard management of context information. The NGSI-LD information model is framed within an ontology and adopts JSON-LD as serialization format for context information. This paper presents an approach to the implementation of the NGSI-LD specification over a SPARQL Event Processing Architecture. This work is being developed within the European-Brasilian H2020 SWAMP project focused on implementing an Internet of Things platform providing services for smart water management in agriculture

Location-aware Mobile Services for a Smart City: Design, Implementation and Deployment

A smart city is a high-performance urban context, where citizens are more aware of, and more integrated into the city life, thanks to an intelligent city information system. In this paper we design, implement and deploy a smart application that retrieves and conveys to the user relevant information on the user's surroundings. This case study application let us discuss the challenges involved in creating a location-aware mobile service based on live information coming from the city IT infrastructure. The service, that is currently being deployed in the Italian city of Cesena, has been designed with the goal of being a general model for future applications. In particular, we discuss location-aware and mobile development, cloud and cluster based geographical data storage, and spatial data computation. For each of these topics we provide implementation and deployment solutions based on currently available technology. In particular we propose an architecture based on a complex On-Line Transaction Processing (OLTP) infrastructure. Furthermore, this paper represents the first comprehensive, scientific study on the subject

Lightweight Scheme for Smart Home Environments using Offloading Technique

Internet of Things (IoT) as an emerging technology has been transforming the different aspects of our world from simple preprogrammed coffee machine to smart farming. Due to the human nature to simplify and ease of living, human are becoming dependent on these automated IoT devices and smart environments like smart phones, wearable devices, smart home and etc. In order to provide better QoS, these devices needs to work together and share data among them, also to the service providers and the cloud. Since these devices are resource constrained, IoT technology heavily depends on the cloud for processing, analytics and storage. But these data coming from the devices contains lot of personal identity information (PII). Almost all the time, the users of these devices are unaware of these information that is being transmitted or they do not possess the control over the data that they are being sent to the service provider, as well as to the cloud. Even the cloud services and service providers are secured but they are always curious. There are lot of security measures implemented for end to end communication but IoT lacks the mechanism for securing the data that the devices are generating along with access control. In this article we are proposing an approach for the security, privacy and access control of user data using Attribute Based Encryption (ABE) in smart home as the case study

DreamCAM: A FPGA-based platform for smart camera networks

International audience—The main challenges in smart camera networks come from the limited capacity of network communications. Indeed, wireless protocols such as the IEEE 802.15.4 protocol target low data rate, low power consumption and low cost wireless networking in order to fit the requirements of sensor networks. Since nodes more and more often integrate image sensors, network bandwidth has become a strong limiting factor in application deployment. This means that data must be processed at the node level before being sent on the network. In this context, FPGA-based platforms, supporting massive data parallelism, offer large opportunities for on-board processing. We present in this paper our FPGA-based smart camera platform, called DreamCam, which is able to autonomously exchange processed information on an Ethernet network

Universal "Chip Based Smart Card" Snooping Device

The objective of this project is basically to design, build and test a Universal "Chip Based Smart Card" Snooping Device. This device would function to notify its user of the actual communication between the smart card and the smart card reader. The existence of this device not only serves as an educational tool but also saves a lot of time and money that are spent on debugging by smart card manufacturing companies. In addition to that, technological advances in the smart card world can also be sped up with the help of this device for research and testing. The hardware design of the project has been divided into 3 main sections, the snooping module, the communication module and the processing module. The snooping module taps the data, the communication module formats, encodes and transfers the data to the processing module, and lastly the processing module translates the data into useful information and display's it. The project has been divided into two major milestones where the first one was to set up the snooping device prototype with the processing module being a Computer. The second milestone on the other hand is the final design itself which would be to replace the Computer with a PALM in order to make it portable and affordable. This report gives a complete and detailed illustration on the hardware and software design process for the Universal "Chip Based Smart Card" Snooping Device. All aspects from the design decision, the underlying transmission protocols and also programming logics have been dissected and elaborately explained in the report. The design presented is a complete working device that fulfills all the objectives that have been set. The hardware device is certainly good enough to be marketed as it works flawlessly and achieves the most important objective of the project, which is to obtain the data transfer between the card and the smart card reader

Enhancing Security and Privacy on Smart City’s Collected Data: A Fog Computing Perspective

Smart cities use information and communication technologies to deliver services to their citizens. Use of ICT makes them to be more intelligent and efficient in usage of resources, resulting in cost and energy savings, improved service delivery and quality of life. Smart cities are expected to be the fundamental pillars of continued economic growth and improved services delivery. Smart City technology is having ability to constantly gather information about the city, sharing the data with people, devices and technologies or borrowing relevant data from elsewhere, for analysis to enable informed decision making. For instance internet of things has emerged as a technological driving force in real time service delivery in smart cities. These applications provide new abilities, enhancing monitoring, and provision of action oriented process on control and device management. Smart devices are a major source of big data in smart cities. With expected increase of billions of smart devices and sensors in smart city by the year 2020, more data will be generated which will reduce efficiency of cloud access, due to increased volume. Security and privacy of data is a challenge in smart city, negligence in data security and privacy can be amplified in folds resulting to faulty applications, services along with paralyzing the entire city through Denial of Service (DDoS) attack, Spear Phishing Attacksand Brute-Force Attacks among others.Fog computing FC is a new paradigm that is intended to extend cloud computing CC through deployment of processing and localized units into the network edge, enabling low latency, offering location awareness and latency sensitiveness. Homomorphism for encryption, authorization, authentication, and classification are performed on collected data in smart cities to improve security and privacy. In this paper assimilation and analysis, is performed with fog computing aspects of decentralization, different policies for datacenter transferstrategies being analyzed.Processing time, access time, request time, response time and cost analysis show system efficiency

Enhancing Security and Privacy on Smart City’s Collected Data: A Fog Computing Perspective

Smart cities use information and communication technologies to deliver services to their citizens. Use of ICT makes them to be more intelligent and efficient in usage of resources, resulting in cost and energy savings, improved service delivery and quality of life. Smart cities are expected to be the fundamental pillars of continued economic growth and improved services delivery. Smart City technology is having ability to constantly gather information about the city, sharing the data with people, devices and technologies or borrowing relevant data from elsewhere, for analysis to enable informed decision making. For instance internet of things has emerged as a technological driving force in real time service delivery in smart cities. These applications provide new abilities, enhancing monitoring, and provision of action oriented process on control and device management. Smart devices are a major source of big data in smart cities. With expected increase of billions of smart devices and sensors in smart city by the year 2020, more data will be generated which will reduce efficiency of cloud access, due to increased volume. Security and privacy of data is a challenge in smart city, negligence in data security and privacy can be amplified in folds resulting to faulty applications, services along with paralyzing the entire city through Denial of Service (DDoS) attack, Spear Phishing Attacksand Brute-Force Attacks among others.Fog computing FC is a new paradigm that is intended to extend cloud computing CC through deployment of processing and localized units into the network edge, enabling low latency, offering location awareness and latency sensitiveness. Homomorphism for encryption, authorization, authentication, and classification are performed on collected data in smart cities to improve security and privacy. In this paper assimilation and analysis, is performed with fog computing aspects of decentralization, different policies for datacenter transferstrategies being analyzed.Processing time, access time, request time, response time and cost analysis show system efficiency