BHiveSense: An integrated information system architecture for sustainable remote monitoring and management of apiaries based on IoT and microservices

Precision Beekeeping, a field of Precision Agriculture, is an apiary management strategy based on monitoring honeybee colonies to promote more sustainable resource usage and maximise productivity. The approach related to Precision Beekeeping is based on methodologies to mitigate the stress associated with human intervention in the colonies and the waste of resources. These goals are achieved by supporting the intervention and managing the beekeeper’s timely and appropriate action at the colony’s level. In recent years, the growth of IoT (Internetof-Things) in Precision Agriculture has spurred several proposals to contribute to the paradigm of Precision Beekeeping, built on different technical concepts and with different production costs. This work proposes and describes an information systems architecture concept named BHiveSense, based on IoT and microservices, and different artefacts to demonstrate its concept: (1) a low-cost COTS (Commercial Off-The-Shelf) hive sensing prototype, (2) a REST backend API, (3) a Web application, and (4) a Mobile application. This project delivers a solution for a more integrated and sustainable beekeeping activity. Our approach stresses that by adopting microservices and a REST architecture, it is possible to deal with long-standing problems concerning interoperability, scalability, agility, and maintenance issues, delivering an efficient beehive monitoring system.info:eu-repo/semantics/publishedVersio

Standardization Roadmap for Unmanned Aircraft Systems, Version 1.0

This Standardization Roadmap for Unmanned Aircraft Systems, Version 1.0 (“roadmap”) represents the culmination of the UASSC’s work to identify existing standards and standards in development, assess gaps, and make recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D. The roadmap has examined 64 issue areas, identified a total of 60 gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that total, 40 gaps/recommendations have been identified as high priority, 17 as medium priority, and 3 as low priority. A “gap” means no published standard or specification exists that covers the particular issue in question. In 36 cases, additional R&D is needed. The hope is that the roadmap will be broadly adopted by the standards community and that it will facilitate a more coherent and coordinated approach to the future development of standards for UAS. To that end, it is envisioned that the roadmap will be widely promoted and discussed over the course of the coming year, to assess progress on its implementation and to identify emerging issues that require further elaboration

Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0

This Standardization Roadmap for Unmanned Aircraft Systems, Version 2.0 (“roadmap”) is an update to version 1.0 of this document published in December 2018. It identifies existing standards and standards in development, assesses gaps, and makes recommendations for priority areas where there is a perceived need for additional standardization and/or pre-standardization R&D. The roadmap has examined 78 issue areas, identified a total of 71 open gaps and corresponding recommendations across the topical areas of airworthiness; flight operations (both general concerns and application-specific ones including critical infrastructure inspections, commercial services, and public safety operations); and personnel training, qualifications, and certification. Of that total, 47 gaps/recommendations have been identified as high priority, 21 as medium priority, and 3 as low priority. A “gap” means no published standard or specification exists that covers the particular issue in question. In 53 cases, additional R&D is needed. As with the earlier version of this document, the hope is that the roadmap will be broadly adopted by the standards community and that it will facilitate a more coherent and coordinated approach to the future development of standards for UAS. To that end, it is envisioned that the roadmap will continue to be promoted in the coming year. It is also envisioned that a mechanism may be established to assess progress on its implementation

A case study of the Army Reverse Auction

Acquisition reform has attempted to change the procurement process over the past several years. Some believe the reform measures have been changes in policy or revisions of a paperwork process. The draw down of the workforce and financial constraints demand acquisition professionals conduct business in a smarter, more efficient manner. The technology today provides Internet platforms that allow the commercial marketplace to take advantage of electronic commerce. The Army has implemented a reverse auction program designed to capture many of the practices in use in the commercial industry. Foremost, dynamic pricing replaces fixed pricing models observed in traditional procurement strategies. Reverse auctions offer the Government the means to replicate a successful commercial practice that is becoming the accepted way of doing business. This thesis reviews performance of the Army's Reverse Auction pilot program after its first year of use. Three buying cases and 40 other reverse auctions are reviewed. The comparative analysis identifies commonalities for success and differences between past experiences with the reverse auction. The thesis concludes acquisitions for items that resemble commercial products and based on price are most successful in reverse auctions. The 43 auctions reviewed resulted in $1,606,393 saved. The mean savings was 21.83% for the auctions reviewed.http://archive.org/details/acasestudyofarmy109451098

Dynamic Target Classification in Wireless Sensor Networks

Information exploitation schemes with high-accuracy and low computational cost play an important role in Wireless Sensor Networks (WSNs). This thesis studies the problem of target classification in WSNs. Specifically, due to the resource constraints and dynamic nature of WSNs, we focus on the design of the energy-efficient solutionwith high accuracy for target classification in WSNs. Feature extraction and classification are two intertwined components in pattern recognition. Our hypothesis is that for each type of target, there exists an optimal set of features in conjunction with a specific classifier, which can yield the best performance in terms of classification accuracy using least amount of computation, measured by the number of features used. Our objective is to find such an optimal combination of features and classifiers. Our study is in the context of applications deployed in a wireless sensor network (WSN) environment, composed of large number of small-size sensors with their own processing, sensing and networking capabilities powered by onboard battery supply. Due to the extremely limited resources on each sensor platform, the decision making is prune to fault, making sensor fusion a necessity. We present a concept, referred to as dynamic target classification in WSNs. The main idea is to dynamically select the optimal combination of features and classifiers based on the probability that the target to be classified might belong to a certain category. We use two data sets to validate our hypothesis and derive the optimal combination sets by minimizing a cost function. We apply the proposed algorithm to a scenario of collaborative target classification among a group of sensors which are selected using information based sensor selection rule in WSNs. Experimental results show that our approach can significantly reduce the computational time while at the same time, achieve better classification accuracy without using any fusion algorithm, compared with traditional classification approaches, making it a viable solution in practice

Cyber Risk Assessment and Scoring Model for Small Unmanned Aerial Vehicles

The commercial-off-the-shelf small Unmanned Aerial Vehicle (UAV) market is expanding rapidly in response to interest from hobbyists, commercial businesses, and military operators. The core commercial mission set directly relates to many current military requirements and strategies, with a priority on short range, low cost, real time aerial imaging, and limited modular payloads. These small vehicles present small radar cross sections, low heat signatures, and carry a variety of sensors and payloads. As with many new technologies, security seems secondary to the goal of reaching the market as soon as innovation is viable. Research indicates a growth in exploits and vulnerabilities applicable to small UAV systems, from individual UAV guidance and autopilot controls to the mobile ground station devices that may be as simple as a cellphone application controlling several aircraft. Even if developers strive to improve the security of small UAVs, consumers are left without meaningful insight into the hardware and software protections installed when buying these systems. To date, there is no marketed or accredited risk index for small UAVs. Building from similar domains of aircraft operation, information technologies, cyber-physical systems, and cyber insurance, a cyber risk assessment methodology tailored for small UAVs is proposed and presented in this research. Through case studies of popular models and tailored mission-environment scenarios, the assessment is shown to meet the three objectives of ease-of-use, breadth, and readability. By allowing a cyber risk assessment at or before acquisition, organizations and individuals will be able to accurately compare and choose the best aircraft for their mission