People-Centred Development of a Smart Waste Bin - PMC

The survey was completed by 194 respondents. Of these, 71% were women, 27% were men and 2% did not wish to identify themselves by gender. In terms of age structure, the majority of respondents were aged between 41 and 60 years old with 39%, followed by those aged between 21 and 40 years old with 33%, those aged 61 and over with 19% and those aged under 20 years old with 8%. In terms of educational structure, the majority of respondents were highly educated, with 84% having a Master&#;s or PhD degree, a post-secondary education, a college or a university degree, while only 8% having a secondary education, 1% having a vocational education and 7% having a primary education. The survey was mainly responded to by the active population, i.e., employed or working people.

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5.2. Survey Results

In the research, we were interested in the extent to which participants were willing to act in an environmentally friendly manner and to what extent they actually do so. The results showed that participants at the declarative level showed a high level of environmental awareness and were very much willing to handle waste appropriately, where the mean value was 4.56. This was not surprising, since people often express a high level of awareness (or, as Beckmann [32] wrote, &#;who would actually dare to admit a lack of interest in environmental problems or an environmentally unfriendly attitude?&#;). One of the proofs of this arose quickly&#;the impression of a positive attitude towards the environment began to fade when participants were asked about actual environmental action. The average value of the demonstrated actual environmental position was 4.31. The transition to one&#;s own active participation in solving environmental problems thus expressed the gap between those who expressed their commitment to environmental protection only at the level of attitudes and those for whom caring for the environment actually held value (Table 1). This result is largely consistent with the results of similar research to date on the gap between environmental awareness and behaviour [4,33,34]. The Table 1 shows the willingness to behave in an environmentally friendly manner on a hypothetical and active level where the respondents (N = number of respondents) answered how much they agreed with the statement with the help of a Likert scale (1&#;completely insignificant, 2&#;insignificant, 3&#;medium, 4&#;important, 5&#;very important).

Table 1.

Willingness to behave in an environmentally friendly manner on a hypothetical and active level.

Statement N 1 2 3 4 5 Mean Value Standard Deviation &#;I am willing to handle waste even more conscientiously&#; 193 0.5% 0% 8.3% 24.9% 66.3% 4.56 0.69 &#;I regularly separate waste in my household and I strive to produce as little as possible.&#; 194 0.5% 1.0% 9.3% 44.9% 44.3% 4.31 0.726 Open in a new tab

The results of the survey (Figure 4) showed that people rate the waste bin with normative information as more suitable for waste management with 59%, and the waste bin with emotional information as less suitable by 41% of correspondents.

Figure 4.

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Normative vs. emotional information presentation.

Based on the t-test of independent samples, we found that responses of the study participants regarding the choice of normative (index 1) and emotional (index 2) intervention in terms of their gender, age and educational structure did not differ statistically significantly, however, certain interesting differences between the individual groups of participants were indicated. Regarding the gender structure, both genders evaluated the choice of the type of intervention practically equally. Both genders largely preferred a normative intervention with a mean value of 1.40 (mean of the indexes 1 and 2) for women and 1.41 for men (Table 2).

Table 2.

Gender and normative vs. emotional information presentation (index 1 = normative intervention, index 2 = emotional intervention).

Gender N Mean Value Standard Deviation female 53 1.40 0.494 male 136 1.41 0.494 Total 189 1.41 0.494 Open in a new tab

However, younger respondents rated higher the waste bin with the emotional (index 2) and more personal appeal, while older respondents rated higher the one with the normative appeal (index 1). Under 20-yearsold respondents rated the waste bin with the emotional intervention as more appropriate for promoting waste management, on an average 1.56 (mean of the indexes 1 and 2). Those aged 21 to 40 rated the normative intervention as more appropriate on an average 1.44. Participants aged 41 to 60 (on an average 1.37), and over 61 (on an average 1.38) rated the normative version of the waste bin higher than the emotional version (Table 3).

Table 3.

Age and normative (index 1) vs. emotional information (index 2) presentation.

Age N Mean Value Standard Deviation to 20 years old 16 1.56 0.512 from 21 to 40 years old 64 1.44 0.500 from 41 to 60 years old 76 1.37 0.486 more than 61 years old 37 1.38 0.492 Total 193 1.41 0.493 Open in a new tab

In terms of education, those with a university or higher education rated the normative waste bin higher than the older ones, with on average 1.38 (mean of the indexes 1 and 2). Those with a secondary education rated the emotional appeal more highly with on average 1.60. Those with a vocational education were completely unanimous in their preference for the emotional appeal waste bin, while those with a primary education also rated the emotional appeal higher than the normative one, with an average of 1.57 (Table 4).

Table 4.

Education and normative (index 1) vs. emotional (index 2) information presentation.

Education Mean Value N Standard Deviation primary school 1.57 14 0.514 vocational education 1.00 1 secondary education 1.60 15 0.507 university or higher education 1.38 163 0.487 Total 1.41 193 0.493 Open in a new tab

In studying the role of individual constructs of psychological variables, values, attitudes, personal norms, subjective norms and perceived behavioural control in the choice of normative or emotional intervention, we found that within the values, altruistic and biosphere values were those that influenced the choice of normative intervention. Conversely, hedonic and biospherical values were the ones that most influenced the choice of emotional intervention. This result is not surprising, as hedonic values are those that are reflected in positive and emotionally related orientations, such as a joy of life, comfort and enjoyment [35]. Biosphere values, on the other hand, are linked to orientations such as a coexistence with nature, environmental protection, and are thus surprisingly positively linked to appropriate waste management, regardless of the intervention we used, whether emotionally or normatively. On the other hand, altruistic values, which are reflected in orientations such as equality and justice, are more closely linked to social and personal norms, collective social orientations and concern for the well-being of all people in the world. According to attitudes, there were no significant differences in their impact on selection. On the other hand, personal and subjective norms had a more visible influence on the selection. Thus, those who preferred normative intervention valued personal norms and subjective norms to a greater extent. Which is not surprising, since human norms are reflected in an individual&#;s sense of moral duty to act in an environmentally friendly manner and relate to their perception of what is &#;appropriate&#; in a given situation [36]. The participants also highly valued perceived behavioural control, which was reflected in their own ability to act in an environmentally friendly manner. The reason for this may be that normative intervention, when communicating certain information to participants, in our case the amount of separately collected waste in Ljubljana, encourages people to feel their own ability and a sense of higher capacity for environmentally friendly behaviour (Table 5). In terms of intention and actual behaviour, the results show that those with a higher intention to act environmentally friendly and actually behave in this way were more likely to choose the normative intervention.

Table 5.

Psychological factors, intention, behaviour and normative (index 1) vs. emotional (index 2) information presentation.

Constructs N Mean Value Standard Deviation altruistic values normative intervention 114 4.88 0.29 emotional intervention 79 4.75 0.43 egoistic values normative intervention 114 2.72 0.72 emotional intervention 79 2.80 0.68 hedonic values normative intervention 114 4.14 0.69 emotional intervention 79 4.35 0.61 biospheric values normative intervention 114 4.62 0.56 emotional intervention 79 4.66 0.56 attitudes normative intervention 114 4.59 0.47 emotional intervention 79 4.60 0.46 personal norm normative intervention 114 4.45 0.59 emotional intervention 79 4.21 0.76 subjective norm normative intervention 114 4.07 0.86 emotional intervention 79 3.78 0.72 perceived behavioural control normative intervention 114 4.21 0.58 emotional intervention 79 4.12 0.59 actual behaviour normative intervention 114 4.32 0.72 emotional intervention 79 4.29 0.74 behavioural intention normative intervention 114 4.57 0.73 emotional intervention 79 5.56 0.63 Open in a new tab

The rise of the smart city has seen numerous innovations over the past decade, with a range of advanced technologies being introduced to improve and streamline city infrastructure. Spanning many different systems, including energy, transportation, and internet connectivity to name a few, they aim to make urban areas more accessible to everyone that inhabits them. With global waste projected to increase by 69% before and a growing commitment from over 80% of businesses towards environmental sustainability, the need for improved waste and recycling management is more pressing than ever to achieve zero waste goals.

Smart cities like New York, Barcelona, and London, in tandem with Internet of Things (IoT) technologies, are leading the way in promoting more efficient urban living. Among the various sectors benefiting from these technologies, smart waste management is emerging as a crucial element in enhancing the livability and sustainability of municipalities around the world. 

The journey from the generation and collection of waste to its diversion and processing is becoming more efficient, thanks in part to the introduction of smart recycling bins. These bins represent a significant step in cleaning up urban landscapes and streamlining waste management systems. Innovations in this sector, including AI-powered solutions like Pello, are transforming operational costs and waste management benchmarks, offering deeper insights into the lifecycle of waste. As we explore what smart garbage bins are and how they function, it&#;s clear that such technologies are pivotal in shaping the future of sustainable urban living. But what exactly are smart garbage bins and how do they work? Read on to learn the answer to these questions and more.

 

What Is a Smart Recycling Bin?

A smart recycling bin is an innovative and technologically advanced version of a traditional waste bin, with the ultimate aim of sending less waste to landfill. It is equipped with various sensors, connectivity features, and data analytics capabilities to improve waste management and recycling efforts. They are designed to make the waste collection and recycling process more efficient, convenient, and sustainable for both businesses and consumers.  

In addition to sensors and data capture features, a smart recycling bin may also include auto sorting technologies and a compactor. Often, these features are supported by AI technologies that can efficiently identify waste types and send them to the right containers. Once the containers are full, the smart bin can be emptied, and waste streams easily diverted to the correct recycling facility.  

 

How Do Smart Waste Bins Work?

 

Today, there is a range of different smart bins available, each with a different set of features that enhance functionality over that of a conventional trash can. However, broadly speaking, most smart bins work in the same way.

 

Features of A Smart Recycling Bin

While different smart bins offer different features, there is a core set of elements that turns a conventional trash can into a smart bin. Below we cover these core features in more detail.

Sensors

Smart bins are equipped with sensors that can detect the fill level of the bin. This information is often transmitted wirelessly over WiFI or Bluetooth, allowing waste management teams to optimize collection routes and reduce unnecessary pickups. Cameras and other sensors may also detect the type of waste being placed in the bin.

Connectivity

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Smart bins are connected to the Internet of Things (IoT), enabling real-time communication between the bins, waste management teams, and central control systems. This connectivity also allows data collection and analysis.

Data Analytics

The data collected from the smart bins, such as fill levels, types of waste, and location, can be analyzed to identify patterns and trends. This information can help in making informed decisions about waste collection schedules, recycling campaigns, and resource allocation.

Notifications

Some smart bins can send notifications to waste management teams when they are nearing full capacity. This helps optimize collection routes and prevents overflow, reducing environmental impact.

 

Benefits of Smart Waste Bin Technology

Smart waste bins offer a huge range of benefits over conventional waste management solutions, ensuring that more waste is sorted before it reaches recycling facilities. Some of the benefits include: 

 

Efficient Waste Collection

Traditional waste collection methods often involve fixed schedules or routes, which can lead to unnecessary trips and wasted resources. Smart bins, equipped with fill-level sensors and IoT connectivity have the potential to disrupt this approach to waste management by continuously monitoring fill levels and transmitting real-time data to waste management operators.

This data provides insights into the rate of waste accumulation, enabling operators to create dynamic collection routes. Instead of collecting from bins on predetermined schedules, waste management teams can now prioritize bins that are nearing full capacity. By doing so, they reduce the number of collection trips and minimize the carbon emissions associated with fuel consumption.

 

Data-Driven Insights

The data collected by smart waste bins goes beyond just optimizing collection routes, offering a rich vein of information for improved waste management strategies and enabling evidence-based decision-making. By analyzing the patterns and trends in waste generation and disposal, waste management teams gain valuable insights into the behaviors of communities and individuals.

For instance, data might reveal peak waste generation times, allowing for better resource allocation during these periods. Moreover, understanding the types of waste being disposed of most frequently can guide the development of targeted recycling campaigns. By tailoring educational initiatives to address prevalent waste disposal habits, recycling efforts become more effective and impactful.

 

Behavioral Change

One of the most interesting impacts of smart waste bins is their ability to influence individual behavior. Through real-time feedback mechanisms, these bins encourage people to be more conscious of their waste disposal habits, and when users see that their actions directly impact the fill levels of bins and the efficiency of waste collection, they are more likely to adopt responsible waste disposal practices. 

This behavioral shift extends beyond just using the smart bins correctly, and it can inspire a broader shift towards sustainability in daily life. As users become accustomed to this type of feedback loop, they may start to consider waste reduction and recycling in other aspects of their routines. 

 

Cost Savings

Optimized collection routes mean fewer trips, reduced labor, and lower fuel expenses, meaning cost savings for any waste management team or company. In addition, by preventing overflow and littering, additional costs associated with cleanup and maintenance can be reduced. 

These cost savings align with broader sustainability goals, with efficient resource utilization reducing the waste management industry&#;s environmental footprint, making it more sustainable and responsible.

 

Smart Bins &#; Looking to the Future

While smart bins are already packed with the latest tech, advancing technologies look set to push the concept further. In the future, more smart bins are likely to be fitted with AI operating systems, allowing the device to actively learn, and subsequently cleaning, sorting, and crushing all types of waste more efficiently. In addition, improved data analytics will allow a better understanding of waste generation, allowing both businesses and consumers to identify ways to reduce and eliminate unnecessary waste.

However, while these elements may be seen as the next mainstream features, as smart cities continue to develop it is hoped that innovation will keep pace, and as smart trash bins continue to improve recycling rates, they may get even smarter!

 

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