Consumers are willing to pay a price for explainable, but not for green AI. Evidence from a choice-based conjoint analysis

A major challenge with the increasing use of Artificial Intelligence (AI) applications is to manage the long-term societal impacts of this technology. Two central concerns that have emerged in this respect are that the optimized goals behind the data processing of AI applications usually remain opaque and the energy footprint of their data processing is growing quickly. This study thus explores how much people value the transparency and environmental sustainability of AI using the example of personal AI assistants. The results from a choice-based conjoint analysis with a sample of more than 1.000 respondents from Germany indicate that people hardly care about the energy efficiency of AI; and while they do value transparency through explainable AI, this added value of an application is offset by minor costs. The findings shed light on what kinds of AI people are likely to demand and have important implications for policy and regulation.

Analysis of Regional Water and Energy Consumption Considering Economic Development

The evaluation of regional water and energy consumption is of great significance to improving regional resource utilization. This paper analyzed the water and energy footprints in different provinces of China, considering regional economic levels. The results indicate: (1) both the largest water footprint and water footprint per capita were in Xinjiang and agriculture had the largest value; (2) Shandong was the largest energy consumer, Ningxia had the largest energy footprint per capita, and coal occupied the largest proportion for the top five energy footprint provinces; and (3) the resource input–output efficiencies in Beijing and Fujian were high, while water and energy consumption were low and gross regional product was high, compared with the average value of China. The situations in Xinjiang and Inner Mongolia were opposite. The change of consumption pattern for each inhabitant, the adoption of water-saving technology, and an increase to water-saving awareness would be helpful to decrease regional water consumption. An increase of regional energy use efficiency and a change to reduced energy consumption would contribute to the decreasing of regional energy consumption. More attention should be paid to renewable and clean Energies. In addition to solution from the local perspective, the virtual water trade and the energy product trade may relieve regional resource pressure in some extent, and the possible influencing should be considered at the same time. This paper could provide suggestions for regional resource utilization and sustainable development.

Life Cycle Assessment of Different Prefabricated Rates for Building Construction

In recent years, Sweden has promoted prefabricated buildings supporting the increasing of prefabricated rates in buildings with precast components, in order to reduce the environmental problems caused by the construction sector. This study, focusing on the construction activities, examines how the increasing prefabricated rate could influence the environmental impacts of the construction sector. This study conducts a cradle-to-gate life cycle assessment (LCA) of a reference building with a prefabricated rate of 26% in the Stockholm Royal Seaport, and compares nine scenarios with prefabricated rates, ranging from 6% to 96%. The results indicate the water footprint decreases, but the total energy footprint and carbon footprint increase as the prefabricated rate increases. Among other impacts, terrestrial ecotoxicity shows the biggest increase with an increase of the prefabricated rate. This study reveals that material extraction is the largest influencing factor, causing a water footprint when the prefabricated rate increases. The impact changes in the energy footprint, carbon footprint, and terrestrial ecotoxicity, and are primarily determined by transport and are sensitive to transport distance and vehicle types.

Monitoring Illegal Tree Cutting through Ultra-Low-Power Smart IoT Devices

Forests play a fundamental role in preserving the environment and fighting global warming. Unfortunately, they are continuously reduced by human interventions such as deforestation, fires, etc. This paper proposes and evaluates a framework for automatically detecting illegal tree-cutting activity in forests through audio event classification. We envisage ultra-low-power tiny devices, embedding edge-computing microcontrollers and long-range wireless communication to cover vast areas in the forest. To reduce the energy footprint and resource consumption for effective and pervasive detection of illegal tree cutting, an efficient and accurate audio classification solution based on convolutional neural networks is proposed, designed specifically for resource-constrained wireless edge devices. With respect to previous works, the proposed system allows for recognizing a wider range of threats related to deforestation through a distributed and pervasive edge-computing technique. Different pre-processing techniques have been evaluated, focusing on a trade-off between classification accuracy with respect to computational resources, memory, and energy footprint. Furthermore, experimental long-range communication tests have been conducted in real environments. Data obtained from the experimental results show that the proposed solution can detect and notify tree-cutting events for efficient and cost-effective forest monitoring through smart IoT, with an accuracy of 85%.

IMPACT OF ENERGY EFFICIENCY OF MODERN RESIDENTIAL AREA ON THE ENVIRONMENT

Improving the energy efficiency of facilities should reduce greenhouse gas (GHG) emissions and independence from energy imports, increase jobs and energy security, as well as encourage researchers in further research to be creative, innovative and competitive. With about 40% of primary energy consumption accompanied by 36% of greenhouse gas emissions, the construction sector is one of the largest consumers in Europe. Energy consumption of the construction sector in Serbia has a significant share in total energy consumption of 48%, 65% of which refers to energy consumption in residential buildings. The legislation on Energy efficiency in Serbia implies a specific energy consumption of 65[kWh/m2] for one apartment buildings and 60[kh/m2] for multi-apartment buildings. In this paper, a settlement with 50 apartment buildings is analyzed, impact on building envelope construction and applied heating system type to carbon and primary energy footprint is estimated using the degree-day method. Although the mentioned specific energy consumption limit is determined by national legislation, this paper tackles the benefits and costs of reducing energy and carbon footprint by reducing carbon and primary energy footprint to a value lower than the mentioned limit.

A Novel Pilot Spoofing Scheme via Intelligent Reflecting Surface Based On Statistical CSI

<div>Pilot spoofing attack brings new challenges to physical layer secure transmission. However, this method will not work without any knowledge about the pilot sequence and active eavesdropping can be detected by constructing random pilot sequence. Intelligent reflecting surface (IRS), with the real-time programmable features for wireless channels, provides new possibilities for effective pilot spoofing. In this paper, the IRS is deployed near the legitimate users and the legitimate signal can always be passively reflected. Then the control strategy is embedded into the communication process under time-division duplex mode to assist eavesdroppers to conduct pilot spoofing.</div><div> By setting different phase shifts at the IRS during the uplink phase and downlink phase, the channel reciprocity disappears, and thus secure beamforming vector is biased towards the eavesdropper. Furthermore, in order to overhear more information, the average secrecy rate minimization problem based on statistical channel state information is established by carefully designing the phase shifts, which is non-trivial to solve. With alternating optimization and Charnes-Cooper transformation technique, the original problem is transformed into convex form and a near optimal solution is achieved. Finally, simulation results show that our proposed scheme can pose serious secure threat without any energy footprint. What's more, if the IRS is not utilized by the internal users properly, it will bring more threat. </div>

Operational energy footprint of vehicle

One of the many important challenges of the modern world is the greenhouse effect of CO2. It is necessary to implement solutions that will eliminate it. Since the easiest way to eliminate the greenhouse effect is to reduce hydrocarbons fuel consumption, it is important to evaluate the fuel (energy) consumption in long term operation. The article presents a proposal for the use of the so-called vehicle energy footprint. The method of creating such a trace is presented and illustrated with specific results of data analyzes. The data is publicly available, which means that the presented method can be independently verified. It has also been shown that the use of the method not only organizes the analyzes, but also leads to information that cannot be obtained with other methods. It therefore seems that an attractive tool has been developed for future applications.

Code coagulation is an effective compilation technique for the JVM

Compilers are the interface between programmers and computers. The output of a compiler determines the speed of the resulting program as well as its energy footprint -- of increasing importance in this world of climate change and battery-dependent computing. Code coagulation has the potential to improve that performance, particularly relative to (JIT) interpreters. Java and related languages are in wide use, so addressing their performance has large potential impact. Optijava is an experimental compiler that applies code coagulation to Java programs.

Code coagulation is an effective compilation technique for the JVM

Compilers are the interface between programmers and computers. The output of a compiler determines the speed of the resulting program as well as its energy footprint -- of increasing importance in this world of climate change and battery-dependent computing. Code coagulation has the potential to improve that performance, particularly relative to (JIT) interpreters. Java and related languages are in wide use, so addressing their performance has large potential impact. Optijava is an experimental compiler that applies code coagulation to Java programs.