Informal E-waste recycling practices and environmental pollution in Africa: What is the way forward?

Globally, e-waste is the fastest growing and most valuable waste-stream. While countries worldwide are increasingly acknowledging the e-waste problem and introducing policies and regulations that deal with e-waste, large quantities of e-waste still go undocumented. Much of these global e-wastes are accumulating in open-dumpsites and landfills in African-countries where they are recycled informally resulting in significant environmental and public-health concerns.

Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning.

The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, the municipality is unable to cope with the increase in garbage, and many urban areas are becoming increasingly difficult to manage. The advancement of technology allows researchers to transmit data from municipal bins using smart IoT (Internet of Things) devices.

A systematic review on cross-culture, humor and empathy dimensions in conversational chatbots: the case of second language acquisition.

The advancement of information and communication technologies has led to an increasing use of conversational chatbots in the learning and teaching sector, especially for the second language (L2) acquisition. In the field of second language acquisition, the use of AI chatbots has been explored, mainly studying pedagogical approaches. However, there is a limited study in the development of empathetic strategies for dealing with learners' emotional discomfort, the impact of humor and the consideration of learners' cultural backgrounds.

Artificial intelligence applications for sustainable solid waste management practices in Australia: A systematic review.

Solid waste generation and its impact on human health and the environment have long been a matter of concern for governments across the world. In recent years, there has been increasing emphasis on resource recovery (reusing, recycling and extracting energy from waste) using more advanced approaches such as artificial intelligence (AI) in Australia. AI is a powerful technology that is increasingly gaining popularity and application in various fields.

Medical Waste from COVID-19 Pandemic-A Systematic Review of Management and Environmental Impacts in Australia.

The coronavirus (COVID-19) pandemic has created a global medical emergency. The unforeseen occurrence of a pandemic of this magnitude has resulted in overwhelming levels of medical waste and raises questions about management and disposal practices, and environmental impacts. The amount of medical waste generated from COVID-19 since the outbreak is estimated to be 2.

A Systematic Review of E-Waste Generation and Environmental Management of Asia Pacific Countries.

Due to the rapid increase in the use of electrical and electronic equipment (EEE) worldwide, e-waste has become a critical environmental issue for many governments around the world. Several studies have pointed out that failure to adopt appropriate recycling practices for e-waste may cause environmental disasters and health concerns to humans due to the presence of hazardous materials. This warrants the need for a review of the existing processes of e-waste management.

An assessment of e-waste generation and environmental management of selected countries in Africa, Europe and North America: A systematic review.

Waste generated from electrical and electronic equipment collectively known as e-waste has remained a persistent environmental problem. Globally, approximately 53.6 million tons of e-waste was generated in 2019.

Multi-criteria group decision making for evaluating the performance of e-waste recycling programs under uncertainty.

This paper presents a multi-criteria group decision making approach for effectively evaluating the performance of e-waste recycling programs under uncertainty in an organization. Intuitionistic fuzzy numbers are used for adequately representing the subjective and imprecise assessments of the decision makers in evaluating the relative importance of evaluation criteria and the performance of individual e-waste recycling programs with respect to individual criteria in a given situation. An interactive fuzzy multi-criteria decision making algorithm is developed for facilitating consensus building in a group decision making environment to ensure that all the interest of individual decision makers have been appropriately considered in evaluating alternative e-waste recycling programs with respect to their corporate sustainability performance.