Leveraging IoT for Enhanced E-Waste Collection and Sustainable Recycling: A Smart Waste Management Approach

Abstract

Introduction: The rapid increase in electronic waste poses a significant environmental challenge, necessitating innovative solutions for efficient collection and recycling. When not disposed of correctly, e-waste releases harmful substances such as lead, mercury and cadmium, posing risks to both the environment and human health. This paper examines the role of the Internet of Things in enhancing e-waste management by improving collection methods and raising awareness among households, with IoT-powered solutions such as smart bins equipped with sensors enabling real-time monitoring of e-waste disposal.

Methodology: The study targeted the population of Vizag to evaluate consumer awareness of e-waste. A structured questionnaire was administered to a sample chosen through a combination of random and purposive sampling methods, and the sample of 300 respondents was drawn from diverse socio-economic backgrounds to ensure representativeness. The study is organised around two objectives: to analyze the relationships between demographic variables and recycling practices, and to assess the level of interest and engagement with IoT technologies designed for e-waste management. Chi-square tests were conducted to examine demographic associations, ANOVA was used to compare disposal practices across age groups, and Tukey's HSD post-hoc analysis identified which specific groups differ. The null hypothesis states that there are no significant differences in e-waste disposal practices among different demographic groups.

Results & Discussion: Of 300 respondents, 30% were aged 25-34 and 25% aged 35-44; 52% were female and 48% male; 40% held a bachelor's degree; and 35% reported annual income of Rs.50,000 to Rs.74,999. Awareness was moderate, with 60% having heard of e-waste but only 40% considering themselves knowledgeable, citing social media (45%) and news articles (30%) as primary sources. On disposal, 55% recycle, 30% use the trash, 10% donate and 5% sell. Only 35% were aware of IoT solutions, though 70% indicated they were likely to adopt them. The most cited barriers were lack of information (50%), inconvenience (40%), perceived ineffectiveness (35%) and time constraints (25%). Chi-square tests returned significant results for age group and recycling (15.23, df 6, p = 0.019), education level and awareness (12.45, df 4, p = 0.014) and income level and participation (10.87, df 4, p = 0.028). ANOVA returned F = 8.93 with p = 0.0001, rejecting the null hypothesis.

Conclusion: The study highlights the potential of IoT in improving e-waste management by making collection more efficient and increasing awareness. While many people are aware of e-waste, their understanding of its environmental impact is limited, showing the need for better education. Improper disposal remains a concern, as a significant portion of respondents still throw away electronics instead of recycling them. Although awareness of IoT-based recycling solutions is low, interest in using them is high, especially among younger individuals. Addressing barriers through targeted awareness campaigns and improved access to recycling options can encourage more people to engage in sustainable e-waste management.