FCC Looks for “Fresh Approach” in Combatting Robocalls

As part of its ongoing effort to stem the rise in illegal robocalls, the U.S. Federal Communications Commission (FCC) is now exploring options to block robocalls along every point in the call path.

In a Notice of Proposed Rulemaking (NPRM), the Commission is proposing rule changes that would require service providers to give consumers accurate caller name and other information to minimize the challenge of evaluating calls originating from unknown sources. Additional changes would require originating providers to verify that the caller’s name and other identification information are accurate and secure, thereby supporting consumer trust and confidence.

The NRPM also details potential steps to reduce the number of scam calls originating from outside the U.S., including advanced call blocking analytics, so that consumers can identify when a call is originating from a foreign country.

The FCC’s latest proposal is intended to build on the STIR/SHAKEN caller ID authentication framework, developed by industry to support the goals of the federal Truth in Caller ID Act of 2009.

The Growth of AI Aligns with E-Waste

The rapidly increasing use of technologies based on artificial intelligence (AI) is bringing potentially life-changing benefits to our commercial and industrial industries, as well as to people around the world. However, the promise of AI often clouds our understanding of the impact that AI-driven technologies are having on the environment.

These consequences are highlighted in a recent article posted to the website of The AI Journal. Titled “The Energy Crisis Limiting AI’s Promise: Hidden E-Waste Explosion Ahead,” the article underscores the often-overlooked aspect of AI technology, that is, its dependence on our current energy infrastructure. The article argues that the continued growth of AI will not only overwhelm our energy infrastructure capacity but will also have a disastrous impact on the increase in electronic waste (e-waste).

According to the article, the deployment and use of AI models currently consume an estimated 415 TWh annually. This is the equivalent of 1.5% of global electricity use today, a usage that is expected to at least double by the year 2030. But, beyond data centers, AI is dependent on data generated by devices and sensors leveraging the Internet of Things (IoT) networks. The number of IoT devices is expected to reach 29 billion (yes, that’s “b” as in “billion”!) by the year 2030.

Many IoT devices have a limited shelf life, contributing to the growth in global e-waste. But even more problematic is their current dependence on disposable batteries as an energy source. The article estimates that over 10 billion disposable batteries are produced annually, but that less than 5% of batteries in use are recycled.

This “perfect storm” will likely lead to an estimated 82 million tons of e-waste generated by 2030, not only further impacting the global environment but also constraining the growth of the technology infrastructure needed to support the future growth and deployment of AI technologies.

To offer a light of hope, the article recommends expanding the use of RF wireless power technologies to support increased energy efficiency in AI operations while also addressing growing sustainability challenges. The broader deployment of RF wireless power technology, the article argues, could be the solution to address these and other concerns while eliminating potential barriers to the future growth of AI.

UConn Researchers Investigating Ways to Reduce EM Wave Radiation

Researchers at the College of Engineering at the University of Connecticut (UConn) are actively working to better understand how different wave-absorbent materials can be used to reduce high-level exposure to electromagnetic (EM) wave radiation.

The research on reducing EM wave radiation exposure is highlighted in an article published in mid-October on the website of “UConn Today.” According to the article, Julia Valla, an associate professor in the chemical and biomolecular engineering department, along with her team of students, is evaluating how the use of ion-exchanged zeolites can support the absorption of EM wave radiation.

Not only would the findings potentially help to reduce the potential impact of EM wave radiation exposure on humans, but they might also be used to provide additional radiation protection for military aircraft and naval vessels.

Under the partial sponsorship of the Air Force Office of Scientific Research, Valla is evaluating the structures of four separate zeolites, including Faujasite, Mordenite, Mordenite Framework Inverted, and Linde Type A, and assessing each structure for its absorption, reflection, and transmission characteristics. Valla and her team are then making small changes to each structure in order to improve its performance.

According to Valla, the objective behind the research is to identify the zeolite structure (or structures) that are most effective in absorbing EM wave radiation. Not only would the findings potentially help to reduce the potential impact of EM wave radiation exposure on humans, but they might also be used to provide additional radiation protection for military aircraft and naval vessels.