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At least 559 records · Page 31

Cooperative Clustering Techniques Applied to Contact Graph Routing

Routing in the space internet has to face many unique challenges - from unplanned disconnections and interruptions to predictable intermittent connectivity due to high network mobility and long propagation delays. NASA’s current approach to such routing is Contact Graph Routing (CGR), using a graph formed of prescheduled communication contacts to compute routes through the network. While this approach manages to tackle issues of connectivity and propagation delays, it is a global approach that requires continuous knowledge of the entire network. In a potential future Solar Space Internet (SSI) such an approach on its own cannot scale to large networks with thousands of members. In this presentation we propose clustering as a solution to CGR scalability. Clustering has been used in many networking problems as a way to subdivide the network and allow for localized routing and better scalability. Using techniques from graph theory and game theory, we explore various existing clustering algorithms and adapt them to the Contact Graph Routing setting. Finally, we propose a way to combine multiple algorithms to create a Delay Tolerant Clustering Protocol.

Yael Kirkpatrick↗

Ad Hawk Aerial Connectivity Network

Wildfires in the United States have been increasing significantly in both frequency and size in recent decades, requiring maximal efficiency on the part of wildfire management organizations. However, while the methodology and technology to combat wildfires has improved, theconnectivityinfrastructure in more ruralregionsof the country is either incompatible with newertechnology or altogether non-existent. Due to this, many modern communication methods are rendered uselessin areas where connection is needed most, complicating the overall fire management procedure. To improve communication and logistics between responders on the front lines and headquarters, a team of NASA researchassociateshas developed the schematic for a rapidly deployable mobile ad-hoc internet-enabled Wi-Fi network that can bring stable internet accessto any desired area.

Wi-Fi↗

Toward Time Synchronization in Delay Tolerant Network based Solar System Internetworking

The expanding presence in space will place an increased dependency on networked communications– a scalable communications infrastructure; that is, the Solar System Internet (SSI). Upcoming developments towards a SSI include NASA’s upcoming LunaNet, or lunar Internet, which provides multi-hop multi-path communications using Delay Tolerant Networking (DTN). DTN has been an active area of research and development, particularly in routing, security, and optimization. DTNs are marked by mobility, disconnection, and a wide variance of latencies (propagation and processing delays). In this paper, we outline progress towards a theory of time synchronization across such a network. An underlying assumption of DTN is that the network is time synchronized already, rather than synchronization being provided as a service. While this is necessary for schedule-based routing, which is necessarily prevalent in DTNs, it is so deeply ingrained as to be built into the primary unit of data in DTNs– the bundle. Indeed, a bundle’s creation timestamp and its time to live (called the lifetime) are based on time, and there are special recommendations for systems that lack accurate clocks. The assumption of time synchronization makes sense when limiting considerations to smaller-scale and more traditional space communication. However, just as end-to-end connectivity cannot be guaranteed in DTNs, neither can access to a reference or authoritative clock. In this more general case, it might be necessary to synchronize over time-varying meshes, and perhaps even to consider relativistic effects. Moreover, by imposing synchronization restrictions in order to sustain a network, the effectiveness of the network to achieve scalability will be necessarily muted. To work towards a time synchronization theory for DTNs, we build upon past successes in modeling DTNs using time-varying graphs and sheaves. This includes error and limitation estimation, which allows one to define domains over which schedule-based routing is possible, up to some threshold sensitivity. Despite the theoretical nature of these results, the approaches taken are also algorithmic, and hence lend themselves to practical implementations. The paper concludes with comparisons of the various methods along with suggestions for future work.

Delay Tolerant Networking↗

Cooperative Clustering Techniques For Space Network Scalability

Routing in the space internet must face many unique challenges - from unplanned disconnections and interruptions to predictable intermittent connectivity due to high network mobility and long propagation delays. NASA’s current approach to such routing is Contact Graph Routing (CGR), using a graph formed of prescheduled communication contacts to compute routes through the network. While this approach manages to tackle issues of connectivity and propagation delays, it is a global approach that requires continuous knowledge of the entire network. In a potential future Solar Space Internet (SSI) such an approach on its own cannot scale to large networks with thousands of members. In this paper we propose clustering as a solution to CGR scalability. Clustering has been used in many networking problems as a way to subdivide the network and allow for localized routing and better scalability. Using techniques from graph theory and game theory, we explore various existing clustering algorithms and adapt them to the Contact Graph Routing setting. We propose a way to combine multiple algorithms to create a Delay Tolerant Clustering Protocol (DTCP). In addition, we explore the underlying networking mechanisms such as multicast, neighbor discovery, and software defined networking that may be used to enable DTCP.

Delay Tolerant Networking↗

Novel Observing Strategies (NOS) and Earth System Digital Twins (ESDT) for Disaster Resilience

"Earth systems have now been observed continuously for more than 50 years, not only from space but also from airplanes, balloons and in-situ sensors. With the addition of commercial remote sensing providers, many more Internet-of-Things sensors and new NASA and international observatories being planned, these incredible amounts of data will soon be augmented by even larger amounts of diverse data and therefore will become more and more difficult to access, integrate, understand and utilize. At the same time, because of climate change and its impacts, in order to predict, manage, and mitigate the effects of extreme science events and disasters, the information produced by all of this data needs to be optimized, organized and analyzed in such a way that it can be utilized by traditional as well as many new non-traditional users. This calls for the development of observing systems that are agile, coordinated and responsive to events of interest, and for information systems to be dynamic, interactive and fast. With these objectives in mind, the Advanced Information Systems Technology (AIST) Program has been developing technologies that will allow for the development of Novel Observing Strategies (NOS) in a distributed, coordinated fashion (i.e., similar to an “Internet-of-Earth-Things”), as well as for the development of novel information systems or Earth System Digital Twins (ESDT) that will build a digital replica of the past and current states of the Earth systems, will derive forecasts of future states under nominal assumptions and will also offer the capability to investigate many hypothetical evolution scenarios under varying impact assumptions. Both NOS and ESDT will be facilitated by the unprecedented advances of Artificial Intelligence technologies, especially Machine Learning (ML), for extracting relevant information from these large amounts of data, for fusing and assimilating diverse data together and for running complex models faster. Together NOS and ESDT will help build the capabilities needed to anticipate, predict and mitigate the effects of future disasters."

Earth Science Remote Sensing; Information Systems↗

2019 Wireless Test Bed Range Manual

Idaho National Laboratory (INL), Next Generation Wireless Test Bed (NGWTB) program, is part of the Critical Infrastructure Protection (CIP) initiative. Our nation’s reliance on wireless and Internet technology is rapidly evolving as more corporations and government agencies, employees, and handheld devices include mobile connectivity for both voice and data. The competitive advantage offered by a mobile workforce is leading many corporations to make wireless integration and convergence a top business priority. Similarly, military systems worldwide are rapidly embracing next-generation commercial technologies to accelerate network-centric capabilities and provide enhanced situational awareness. While handheld devices such as laptops, BlackBerrys, and cell phones once had limited mobility and range, they are rapidly incorporating new and multiple protocols such as Bluetooth, Wi-Fi, Satellite, and broadband cellular (3G/4G) on a single platform to increase their effectiveness and agility. Worldwide there is exponential growth in public Wi-Fi and/or Satellite connectivity access nodes, and 3G/4G cellular continues to evolve and expand the range and speed of these devices. Additionally, critical infrastructure networks, previously isolated or connected with dedicated wireline circuits, are incorporating Zigbee for wireless sensor networks, wireless LANs for maintenance functions, and cellular or Internet based backhaul to manage control centers. Yet with all the build-up surrounding wireless technology, few understand the complexities surrounding wireless protocols and security, the risks of converged network infrastructures, need for interoperability of communication systems, or mitigation measures to safely use and improve new technologies in both commercial and military environments. With no single vendor source for all the telecommunications equipment needed for wireless infrastructure upgrades, and no one entity providing end-to-end testing or independent validation, the INL's NGWTB program fulfills a niche for facilitating integrated testing of multiple technologies, across multiple wireless domains, of next generation wireless telecommunications systems. NGWTB engineers and technicians have constructed and operate domain infrastructure in the Wireless Personal Area Network (WPAN), Wireless Local Area Network (WLAN), Wireless Metropolitan Area Networks (WMAN), and Wireless Wide Area Networks (WWAN). Advantages that make the INL's NGWTB the place to conduct project and programmatic testing include: • NTIA Experimental Station authority • Geographically isolated and low-noise radio frequency (RF) test areas located on a 890 sm DOE reservation • Access to isolated high-speed LAN and FOT networks The rollout of next-generation networks will involve deploying new technologies at every level including new: handsets, frequencies, antenna arrays, cell configurations that are optimized for both data and voice, massive upgrade of cell controllers’ “land-line” phone links from low bandwidth connections to higher capacity fiber or wireless backhaul, and integration of voice switching and Internet/data network protocols (Voice-Over-IP, Web phones). These systems are expected to greatly transform our nation's communications infrastructure and the types of services it provides.

2G↗

Evaluation of Story Maps to Enhance Public Engagement and Communication at Legacy Management Sites - 17334

The US Department of Energy's Office of Legacy Management's (LM) mission is to fulfill the department's post-closure responsibilities and to ensure protection of human health and the environment. Accomplishing that mission currently requires managing 91 legacy sites across the country by performing efficient long-term surveillance and maintenance activities, preserving and making accessible historic site records, and identifying opportunities for beneficial reuse. Integral to the success of these activities is connecting and effectively communicating with the public, governments, and other interested parties. Relationships with such entities are so important that the Office of Legacy Management has elevated such engagement to one of its strategic goals for the next 10 years. Several public engagement efforts are currently supported, including stakeholder meetings, interpretive visitor centers, hard-copy documents, and Internet-based information sources. The tools available to communicate with the public via the Internet are continually improving, and LM proactively evaluates these tools to enhance public engagement. The use of ESRI Story Maps to effectively and more succinctly communicate LM's long-term surveillance and maintenance practices is one tool currently being evaluated. Story Maps can utilize multiple types of content to engage users through site narratives, illustrations of change over time, photos, videos, and embedded links to external sources of information. The ability to illustrate site complexities via graphics and geo-spatial data is particularly useful for staff as well as communicating to stakeholders. Staff with a variety of expertise and functions in the organization can be empowered to respond to stakeholder questions using this tool. In addition, Story Maps can be easily initiated and managed in real time by LM site managers, an efficiency that would be invaluable to them as immediate site communication needs arise. A series of test Story Maps for several sites were developed to explore the capabilities of the tool. The test Story Maps included pages that described site description and overview, historical conditions and use, cleanup conditions, current monitoring data if applicable, and institutional controls. Links to existing communications tools were also incorporated in Story Maps, such as existing web sites that currently store environmental reports and the Geo-spatial Environmental Mapping System (GEMS), where stakeholders can download monitoring data. As with any tool, many things must be taken into consideration, such as: 1) Can the current IT infrastructure support the tool? 2) What data quality protocols need to be established? 2) What resources will be needed to maintain this tool? 3) What type of information should be shared? 4) Who will be responsible for information updates? This paper explores potential approaches for developing and deploying this tool for the public. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Improving the Field Portability of Neutron and Gamma Counting Techniques

Savannah River National Laboratory (SRNL) puts science to work by developing techniques that better meet customers needs for in-situ measurements. There is high demand for laboratory quality measurements in field situations, improving the cost and speed for first responders and environmental monitoring. This work focused on two improvements (1) reading a signal from a neutron detector using a Raspberry Pi (2) testing the Peak-to-Valley method for determining the depth of a source in soil contamination measurements. A Raspberry Pi is a cheap, compact computer. This affordable, compact computer is able to do simple tasks that a desktop computer is able to do, like spreadsheets, browse the internet, play games and even program a simple robot. Additionally, a Raspberry Pi can run off of a battery, so it could be deployed for long term measurements in adverse conditions like neutron monitors deployed in a shipping port. Using the Raspberry Pi and libraries easily accessible on the internet, a code was written in Python that allows the Pi to keep track of how many times a button is pushed. This work will be used with the future goal of creating low power-budget neutron detectors. 1) Make sure Python was correctly installed on the Raspberry Pi. 2) Write a code that will keep track of how many times a button connected to the Pi is pressed. A code was written to use the Raspberry Pi to count the number of times the button was pushed. Moving forward the Raspberry Pi will be tested with a neutron counter. Ideally, each signal from the neutron pulse will be equivalent of 'push the button' and be counted. In the characterization of a soil contamination area both the location and the depth of the source is important. Attenuation of the source by the soil can make determining its depth challenging, particularly for monoenergetic radionuclides like Cs-137. To address this issue, a method of calculating the 'peak-to-valley' ratio of the gamma count spectra is implemented to help calculate the known depth of the source. 1) Determine the 'peak-to-valley' ratio of a Cs-137 source at different depths. 2) Find an appropriate function to serve as a model for the peak-to-valley ratio as a function of depth. Several Petri dishes, filled with sand, were stacked with one containing a Cs-137 source. The individual Petri dishes allowed for the source to be placed at different depths. A bucket was placed over the sand and source, to keep the detector at a consistent height. A Petri dish containing a Eu-155 source, which acted as an internal calibration standard, was placed on top of the bucket. A NaI detector was place on top of the Eu-155 source and the assembly was surrounded by a tungsten shield. Count times were 20 minutes and the data was analyzed using PeakEasy. Data was recorded for Cs-137 at a series of depths in sand. Both exponential and logarithmic functions provided a reasonable fit to the data. The experimental data showed a decreasing 'peak-to-valley' ratio as the depth was increased. The next steps for this project involves determining the optimum fit function and combining the results from sand to different soil types to get a better representation of the soil found at SRS. Eventually, the peak-to-valley ratio will be used to estimate the depth of contamination in field measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Efficient Anomaly Detection Driven By Different Machine Learning Architectures And Models

The rapid growth and ubiquitous adoption of the internet and cyber-physical systems (CPS) have fundamentally transformed modern communication, work, and human-system interactions. While networks now form the backbone of critical digital ecosystems, enabling seamless data transmission across diverse, interconnected systems, this increased connectivity also expands the attack surface, making real-time detection of network intrusions and anomalies a pressing challenge. Detecting unusual activities within network infrastructure requires advanced data traffic analysis to differentiate between legitimate and malicious interactions. Traditional approaches to network anomaly detectionâ??such as rule-based and signature-based systemsâ??often depend on predefined patterns to identify known anomalies, limiting their effectiveness against emerging, stealthy, or previously unseen threats. These conventional methods suffer from high false alarm rates and fail to adapt to the ever-evolving nature of network traffic, particularly in large-scale, decentralized environments where data volume, velocity, and variety are constantly increasing. This dissertation presents artificial intelligence (AI)-driven approaches to anomaly detection that leverage graphics processing unit (GPU)-enabled high-performance computing (HPC) platforms for processing massive network traffic data and monitoring the components of cyber-physical systems (CPS) for potentially hazardous conditions. The research advances several key contributions: (1) Designing efficient machine learning techniques for CPS condition monitoring and anomaly detection; (2) enabling federated learning (FL) frameworks that enable distributed detection while preserving data privacy and system resilience; (3) exploring graph-based methodologies combining graph neural networks (GNN) and graph machine learning (ML) approaches for the Internet of Things (IoT) and automotive network security, and (4) performing distributed edge computing optimizations that integrate FL with scalable technologies for reduced communication overhead. Through extensive experiments, these methodologies demonstrate that complex anomaly detection and condition monitoring tasks can be achieved while balancing computational efficiency and detection accuracy through fine-grained network information processing. The frameworks developed in this research establish a robust foundation for network anomaly detection, providing scalable, adaptive, and privacy-preserving solutions for safeguarding CPS and IoT networks in an increasingly interconnected digital landscape. The practical implications of these research findings are significant, as they can inform the development of next-generation network security systems and contribute to the protection of critical infrastructure against sophisticated cyber attacks.

Marfo, William↗

Thought Leaders during Crises in Massive Social Networks

The vast amount of social media data that can be gathered from the internet coupled with workflows that utilize both commodity systems and massively parallel supercomputers, such as the Cray XMT, open new vistas for research to support health, defense, and national security. Computer technology now enables the analysis of graph structures containing more than 4 billion vertices joined by 34 billion edges along with metrics and massively parallel algorithms that exhibit near-linear scalability according to number of processors. The challenge lies in making this massive data and analysis comprehensible to an analyst and end-users that require actionable knowledge to carry out their duties. Simply stated, we have developed language and content agnostic techniques to reduce large graphs built from vast media corpora into forms people can understand. Specifically, our tools and metrics act as a survey tool to identify thought leaders' -- those members that lead or reflect the thoughts and opinions of an online community, independent of the source language.

97 MATHEMATICS AND COMPUTING↗

IoT in Radiology: Using Raspberry Pi to Automatically Log Telephone Calls in the Reading Room

The work environment for medical imaging such as distractions, ergonomics, distance, temperature, humidity, and lighting conditions generates a paucity of data and is difficult to analyze. The emergence of Internet of Things (IoT) with decreasing cost of single-board computers like Raspberry Pi makes creating customized hardware to collect data from the clinical environment within the reach of a clinical imaging informaticist. This article will walk the reader through a series of basic project using a variety sensors and devices in conjunction with a Pi to gather data, culminating in a complex example designed to automatically detect and log telephone calls.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Semantic Catalog of Things, Services, and Data to Support a Wind Data Management Facility

The purpose of this paper is to discuss how community vocabularies and linked open data best practices are being used to seamlessly link things, data, and off the shelf services to support scientific offshore wind energy research for the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) Wind and Water Power Program. This is largely made possible by leveraging collaborative advances in the Internet of Things (IoT), Semantic Web, Linked Services, Linked Open Data (LOD), and RDF vocabulary communities, which provide the foundation for our design. By adapting these linked community best practices, we designed a wind characterization data management facility capable of continually collecting, processing, and preservation of in situ and remote sensing instrume

atmosphere↗

Correction to: The Importance of Viscous and Interfacial Forces in the Hydrodynamics of the Top-Submerged-Lance Furnace

The article The Importance of Viscous and Interfacial Forces in the Hydrodynamics of the Top-Submerged-Lance Furnace, written by Obiso et al. was originally published electronically on the publisher’s internet portal on July 3, 2019 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on October 3, 2019 to © The Author(s) 2019 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

36 MATERIALS SCIENCE↗

Occupant comfort and behavior: High-resolution data from a 6-month field study of personal comfort systems with 37 real office workers

Personal Comfort Systems (PCS) provide individual occupants local heating and cooling to meet their comfort needs without affecting others in the same space. It saves energy by relaxing ambient temperature requirements for the HVAC system. Aside from these benefits, PCS offers a wealth of data that can describe how individuals interact with heating/cooling devices in their own environment. Recently developed Internet-connected PCS chairs have unlocked this opportunity by generating continuous streams of heating and cooling usage data, along with occupancy status and environmental measurements via embedded sensors. The data allow individuals' comfort and behavior to be learned, and can inform centralized systems to provide ‘just the right’ amount of conditioning to meet occupant needs. In summer 2016, we carried out a study with PCS chairs involving 37 occupants in an office building in California. During the study period, we collected >5 million chair usage data-points and 4500 occupant survey responses, as well as continuous measurements of environmental and HVAC system conditions. The data analysis shows that (1) local temperatures experienced by individual occupants vary quite widely across different parts of the building, even within the same thermal zone; (2) occupants often have different thermal preferences even under the same thermal conditions; (3) PCS control behavior can dynamically describe individuals' thermal preferences; (4) PCS chairs produce much higher comfort satisfaction (96%) than typically achieved in buildings. We conclude that PCS not only provide personalized comfort solutions but also offer individualized feedback that can improve comfort analytics and control decisions in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An energy-aware multiobjective ant colony algorithm to minimize total completion time and energy cost on a single-machine preemptive scheduling

Energy-aware scheduling in manufacturing operations with time-of-use electricity tariffs is a challenging problem. Sustainable manufacturing is gaining significant momentum: companies are not only improving their product quality, but also optimizing the production processes to improve energy consumption (i.e., minimizing energy cost) in order to manage environmental challenges which contribute to global climate change. The purpose of this paper is to study a preemptive scheduling problem on a single-machine to minimize the total completion time and total energy cost under time-of-use electricity tariffs, which is a mixed-integer multiobjective mathematical programming model. To solve these objectives, we develop several new holistic ant colony optimization algorithms. The proposed model is solved via several methods including weighted sum method (WSM) using CPLEX, and multiobjective ant colony optimization based on a dominance ranking (ACO-DR) or based on a dominance ranking procedure and crowding distance comparison (ACO-DRC) or based on a heuristic approach to obtain an approximate Pareto-front and also provide information on when to start and resume each job for any solution on the Pareto-front. We provide detailed experimental results evaluating the performance of the proposed algorithms. In a case study, we demonstrate how the results of the multiobjective model could be utilized in decision making using the multiobjective optimization on the basis of ratio analysis (MOORA) method. Furthermore, this proposed model and heuristics allows decision makers to operate in challenging-data enabled environments in industrial internet of things ecosystem, and assists in optimizing production planning to improve energy cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Using bursty announcements for detecting BGP routing anomalies

Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. Our research shows that BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods of infrequent activity. We hypothesize that we may use these bursty characteristics to detect anomalous routing incidents. In this work, we use manually verified ground truth metadata and volume of announcements as a baseline measure, and propose a burstiness measure that detects prior anomalous incidents with high recall and better precision than the volume baseline. We quantify the burstiness of inter-arrival times around the date and times of four large-scale incidents: the Indosat hijacking event in April 2014, the Telecom Malaysia leak in June 2015, the Bharti Airtel Ltd. hijack in November 2015, and the MainOne leak in November 2018; and three smaller scale incidents that led to traffic interception: the Belarusian traffic direction in February 2013, the Icelandic traffic direction in July 2013, and the Russian telecom that hijacked financial services in April 2017. Our method leverages the burstiness of disruptive update messages to detect these incidents. We describe limitations, open challenges, and how this method can be used for routing anomaly detection.

97 MATHEMATICS AND COMPUTING↗

On legitimacy in impact assessment: An epistemologically-based conceptualisation

Highlights: • Impact assessment (IA) has lost its roots in provision of reliable evidence. • IA is theoretically position ontologically and epistemologically • Theory is used to examine the understanding of legitimacy and finds it to be inadequate. • Recent political decisions show knowledge is missing from understanding of legitimacy. • Knowledge legitimacy is conceptualised to redress the current misunderstandings. - Abstract: Impact assessment (IA) is carried out as an ex ante process to inform decision-making. It includes requirements for engagement with stakeholders (including the public) regarding actions proposed by a proponent. A key issue with the various stakeholders involved is the perceived legitimacy of the IA, which can have implications both for the reputation of the proponent, and the likelihood of conflict over the decision. But the understanding of legitimacy in the IA literature has changed over time in line with an ontological shift from positivism (that scientifically generated information leads to better informed decisions) to the post-positivist acknowledgement of the limitations of scientific method whereby assumptions must be subject to transparency, deliberation and openness. This has led to an epistemological shift towards greater subjectivism which, we suggest, has created new opportunities (which have been realised in political decision-making) to subvert knowledge through the increased use of the Internet and social media. To address the potential for such subversion of legitimacy, we seek to conceptualise legitimacy in the IA context through framing IA around a critical realist ontology and a reliabilist virtue epistemology. This allows us to identify ‘knowledge legitimacy’ as an equally important component of IA legitimacy along with organisational legitimacy. We conceptualise knowledge legitimacy through literature review drawing on rich understandings of knowledge from IA and other fields of research in order to develop a four-dimensional typology. This includes the dimensions of: knowledge accuracy; knowledge restriction; knowledge diffusion; and knowledge spectrum. This is the first theoretically grounded attempt to understand legitimacy in IA. It is hoped that it will provoke discussion in the IA community to further advance theoretical understandings of IA and legitimacy of practice.

54 ENVIRONMENTAL SCIENCES↗

5 G wireless telecommunications expansion: Public health and environmental implications

The popularity, widespread use and increasing dependency on wireless technologies has spawned a telecommunications industrial revolution with increasing public exposure to broader and higher frequencies of the electromagnetic spectrum to transmit data through a variety of devices and infrastructure. On the horizon, a new generation of even shorter high frequency 5G wavelengths is being proposed to power the Internet of Things (IoT). The IoT promises us convenient and easy lifestyles with a massive 5G interconnected telecommunications network, however, the expansion of broadband with shorter wavelength radiofrequency radiation highlights the concern that health and safety issues remain unknown. Controversy continues with regards to harm from current 2G, 3G and 4G wireless technologies. 5G technologies are far less studied for human or environmental effects. }It is argued that the addition of this added high frequency 5G radiation to an already complex mix of lower frequencies, will contribute to a negative public health outcome both from both physical and mental health perspectives. }Radiofrequency radiation (RF) is increasingly being recognized as a new form of environmental pollution. Like other common toxic exposures, the effects of radiofrequency electromagnetic radiation (RF EMR) will be problematic if not impossible to sort out epidemiologically as there no longer remains an unexposed control group. This is especially important considering these effects are likely magnified by synergistic toxic exposures and other common health risk behaviors. Effects can also be non-linear. Because this is the first generation to have cradle-to-grave lifespan exposure to this level of man-made microwave (RF EMR) radiofrequencies, it will be years or decades before the true health consequences are known. Precaution in the roll out of this new technology is strongly indicated. }This article will review relevant electromagnetic frequencies, exposure standards and current scientific literature on the health implications of 2G, 3G, 4G exposure, including some of the available literature on 5G frequencies. The question of what constitutes a public health issue will be raised, as well as the need for a precautionary approach in advancing new wireless technologies.

54 ENVIRONMENTAL SCIENCES↗