Advanced sensors technology survey

This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype

During the last few years, several approaches have been proposed to improve early warning systems for managing geological risk due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements. In this regard, an Artificial intelligence Camera Prototype (AiCP) for real-time monitoring has been integrated in a multisensor monitoring system devoted to rock fall detection. An abandoned limestone quarry was chosen at Acuto (central Italy) as test-site for verifying the reliability of the integratedmonitoring system. A portion of jointed rockmass, with dimensions suitable for optical monitoring, was instrumented by extensometers. One meter of railway track was used as a target for fallen blocks and a weather station was installed nearby. Main goals of the test were (i) evaluating the reliability of the AiCP and (ii) detecting rock blocks that reach the railway track by the AiCP. At this aim, several experiments were carried out by throwing rock blocks over the railway track. During these experiments, the AiCP detected the blocks and automatically transmitted an alarm signal

Generic Home Automation System Using IoT Gateway Based on Wi-Fi and ant+ Sensor Network

This research article explores the use of internet of things (IoT) technology in home automation, including cloud computing and sensor networks to improve quality of life, and the increasing affordability through mobile connectivity. In this proposed smart home system, our main objective is to build a home automation system for the common consumer, which can help him to use home appliances with confidence and control at a low cost. The paper describes the building of an IoT gateway using the ANT multi-hop wireless network protocol and the Wi-Fi protocol, specifically utilizing the nRF24L01 and Esp8266 chips. Various sensor nodes, such as a water tank level sensor, human presence sensor, smart LED door sensor, and smart switch, will be integrated into the system. The main goal of the research is to develop an affordable solution for smart home technology for everyday consumers

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions