Prototype Smart Trash Can for Implementation Smart Environment in the Smart City based on Arduino and Android

Smart trash cans use a proximity sensor (ultrasonic) to detect the height of the trash, the PIR (Passive Infra Red) sensor to detect human presence and Arduino as the data processing center. This trash can also has an LED that functions as an indicator and the buzzer functions as an alarm when the trash can is full. If the garbage reaches half of the trash, the LED will turn yellow, if the garbage reaches a height of 4cm from the trash lid, then the LED will turn red and so the trash can will be locked even though the PIR sensor detects humans. Buzzer will live to attract the attention of cleaning officers to dispose of trash. To dispose of garbage, the clerk needs to shift the open and close trash button so that the lid will open. The author hopes that this smart trash can can increase public awareness to dispose of garbage in its place. The results of study show that PIR sensors work by well in detecting the presence of humans and ultrasonic sensors in detecting the height of garbage are not accurate, so that if the trash if the trash can is empty, sometimes the garbage is minus, whereasif the garbage is < 3.5 cm, the sensor fails detect it.

This research is an implementation of the internet of things (IoT) for smart trash cans in places that are usually visited by many people. Currently, the Covid-19 pandemic in Indonesia is still quite high. Therefore, the Internet of Things (IoT) system is intended to help reduce the spread of the covid-19 virus. This system uses a NodeMCU ESP8266 microcontroller and several sensors that are used to support this research. The design of this IoT system focuses on measuring the distance between the trash can and the person disposing of the trash to calculate the opening and closing distance for the trash and measuring the height of the trash in the trash as a reference for cleaning workers to pick up trash at the right time. This smart trash can can open the lid automatically according to a specified distance and will send an alarm to the cleaning worker smartphone on duty when the height of the trash is full or reaches a predetermined limit.Keywords: Internet of Things, Covid-19, Smart Trash Can, Blynk Platform

This article proposes an autonomous mobile robot (AMR) system based on the artificial intelligence of things (AIoT) for collecting garbage. The proposed system consists of an AMR subsystem, a robot operating system (ROS) robot subsystem, an AI garbage recognition subsystem, solar power supply subsystem, and a smart trash can subsystem. The AMR subsystem uses a motor drive, which is built on an aluminum alloy metal base and is connected to an AI edge computing module via an app, to control the robot. The ROS subsystem is built on an edge computing module, which is coupled with the motor drive module to control the robot arm and the robot gripper, and is connected to the AI edge computing module to control the robot arm through the app. The AI garbage recognition subsystem recognizes the types of waste in real time through an image sensor (camera). This subsystem adopts multiple sensors that can monitor the level of waste in the trash can. Moreover, a map on a web platform locates all trash cans. Servomotors enable automatic opening and closing of the lid to prevent the unpleasant smell of garbage from wafting. A user connects to the AI edge computing module through an app to monitor the robot and control the movement of the robot to any location on the map.

The garbage is collected in dustbin bins. Home and human society trash from all around the world. Our system is set up in such a way that it runs indefinitely gathers real-time data in order to optimize operating time and efficiency. This data will be sent through a wireless mesh network. We offer Trash Management via a Smart Bin System that detects the quantity of waste in the bin in this article. The Smartbin technology was put to the test in the open air. The information gathered sense-making techniques were used to apply data from the trash to improve the efficiency of our smart bin It also contains the information on seasonality is sent to the Municipal Corporation on a daily basis. This allows them to gather data in a more efficient and structured manner. Plastic, recyclable, and organic trash are all types of waste. Human civilization is made of a range of waste products on a regular basis, the majority of which is dry trash, plastic garbage, and recyclable waste are all types of waste. Sewage wastes, household wastes, and so forth. At every corner of the street, in outdoor trash cans and organizations that the municipality maintains. Household Dustbins are used to gather a family's trash, which is then disposed of ensure the garbage is collected and disposed of in the public trash cans society. Because trash in roadside containers is not regulated and collected, our primary goal is to gather correctly most of the time to effectively arrange and manage outdoor trash cans for a clean environment and a sanitary atmosphere.

With the increase in population, the amount of waste generated has increased significantly worldwide and proper waste management has become inevitable. In majority of the cities, trash cans are over flowing due to untimely management of waste. An effective system is required to collect the waste from trash cans and prevent overflow. For cleaner environment and implementation of smart cities, it is essential to reduce overflowing litter cans by a monitoring system. The proposed system keeps track on trash cans and detects the level in it and updates it in a web page. The same could be viewed on a mobile app of the garbage collector and determine the shortest path by linking various routes of the almost full bins. Alerts are produced as in app-notifications for the user. The IoT based garbage monitoring system will enable to maintain a cleaner community.

This community service has been carried out from August to September 2022 in Cikahuripan Village, Cisolok District, Sukabumi Regency. Some of the main problems in Cikahuripan Village are not yet optimal public awareness not to litter, especially throwing garbage in the river. This service aims to increase public awareness of environmental hygiene and health through education and technology. The service is carried out in the form of a seminar entitled "Socialization on the Application of Healthy and Clean Living Behavior" The seminar was held in elementary schools aimed at instilling the importance of cleanliness in the community from an early age, as well as by making automatic trash cans to increase interest in disposing of waste in its place. After the service is completed, it is hoped that the level of concern for some people towards environmental cleanliness and health can continue to increase. In addition, by making trash cans, it is hoped that creativity can continue to grow, especially in the field of technology.Keywords: Environment, Education, Technology

The Smart and Sustainable City Framework (SSCF) redefines the idea of ‘Smart City’ to having “Smart Thinking, Planning and Design” as fundamental for smart and sustainable city development. The framework focuses on the core values of “Smart People, Smart Place, and Smart Planet” that helps shape the city through innovative solutions with technology embedded as an enabler to create a more liveable, walkable, resilient and happy cities for all. Six elements of the Smart and Sustainable City Framework are discussed, which consists of “Smart Living”, “Smart Environment”, “Smart Mobility”, “Smart Infrastructure”, “Smart Governance”, and Smart Economy”. Smart Cultural Precinct (SCP) with the Cultural Triangle at its core in Central, Hong Kong will be used as a case study to demonstrate the use of the SSCF, together with recommendations for Hong Kong and suggestions for the broader application of the SSCF to help shape better cities.

PurposeThe purpose of this paper is to propose a distributed deep learning architecture for smart cities in big data systems.Design/methodology/approachWe have proposed an architectural multilayer to describe the distributed deep learning for smart cities in big data systems. The components of our system are Smart city layer, big data layer, and deep learning layer. The Smart city layer responsible for the question of Smart city components, its Internet of things, sensors and effectors, and its integration in the system, big data layer concerns data characteristics 10, and its distribution over the system. The deep learning layer is the model of our system. It is responsible for data analysis.FindingsWe apply our proposed architecture in a Smart environment and Smart energy. 10; In a Smart environment, we study the Toluene forecasting in Madrid Smart city. For Smart energy, we study wind energy foresting in Australia. Our proposed architecture can reduce the time of execution and improve the deep learning model, such as Long Term Short Memory10;.Research limitations/implicationsThis research needs the application of other deep learning models, such as convolution neuronal network and autoencoder.Practical implicationsFindings of the research will be helpful in Smart city architecture. It can provide a clear view into a Smart city, data storage, and data analysis. The 10; Toluene forecasting in a Smart environment can help the decision-maker to ensure environmental safety. The Smart energy of our proposed model can give a clear prediction of power generation.Originality/valueThe findings of this study are expected to contribute valuable information to decision-makers for a better understanding of the key to Smart city architecture. Its relation with data storage, processing, and data analysis.

Utilising a sequential mixed-method design to investigate the relationship between planning and smart city development; this thesis aims to work toward an integrated response to these challenges through the provision of an evaluative framework for planning smart cities. Such a framework would act as a medium in recommending a future role and direction for the sector of planning and would aim to build upon the opportunities of technology found in smart cities. Such opportunities include improving the weaknesses of traditional-delivery-methods of development in what the thesis broadly views as an analogue approach to the future of cities challenge in a digital world. The thesis employs a grounded-theory approach to data analysis in phase one, before quantitatively analysing planning policy in phase two and comparing these measurements to questionnaire data in phase three to produce an evaluative framework for the role of planning in smart cities. This linkage via sequential steps for data collection and analysis is reflective of the holistic approach of planning as a profession, whereby a consultative process for expertise in the fields of transport, the environment, heritage and infrastructure combine to form a cohesive system of the built environment; leading this thesis to advocate for an introduction of a digital peer if cities are to be smart about their transformation. In being knowledgeable about this transformation the study’s main findings break down the cycle of data in smart cities to data capture, data communication, data processing and data production; before relating these to smart city development principles that combine with the project phases of planning developments to form quadrants, or areas of opportunity, for planning smart cities – building upon the strengths of planning to improve the capacity of cities in operating throughout the new environment of the digital world.

Purpose: The most active and rapid development in today's world is happening in Smart cities. Smart Cities are changing very fast in every aspect, be it development, operations, and or maintenance points of view. Today's Smart Cities are aiming to be at an advanced stage of urbanization and fully exploiting digital infrastructure for rapid urban development. In order to make the cities better places to live and to offer more comfortable and enjoyable living for their residents, Smart Cities are using and employing various tools and technologies to make themselves smarter and more connected with their stakeholders using technology means. Industry 4.0, Digital Transformation, and various latest technologies such as 5G, Data Analytics, IoT, AI, and Machine Learning, Digital Twins, etc. are transforming and shaping up Smart Cities in never before style. In this paper, various such key technologies that are positively affecting Smart Cities are discussed at length. It is also highlighted in detail how these technologies are impacting Smart Cities development and operations. Finally, future research directions are also discussed in brief. Design/Methodology/Approach: Extensive exploration of available literature with research papers, conference papers, white papers, online blogs, dedicated websites, etc. on the research area and interactions with field researchers, subject matter experts, industry professionals is carried out to collect, analyse and process the collected data to find out the facts. The resulted facts and findings about the latest technologies used in Smart Cities is presented in this research paper. Findings/Result: After analysis of available literature and based on interactions with relevant stakeholders and based on own data analysis, it is identified that Smart City services are making use of various latest tools and technologies to solve their real-life challenges. Among vast list of technologies specifically IoT, Blockchain, Digital Twins, 5G, Contactless Technology, AI and ML are found the most significant and widely used technologies in Smart Cities development, operations, and maintenance activities. Originality/Value: It is found that not many research papers are available on analysis of future technologies used in Smart Cities. The data presented in this paper is genuine and original and completely based on systematic literature review, interactions with SME, Researchers and Industry experts and based on own data analysis which produced new findings. Paper Type: Technology oriented Research

This research discusses the efforts of the Penajam Paser Utara Government through the Communication and Information Service in the development of a smart city. Departing from the potential, advantages and capabilities of the region, Penajam Paser Utara is one of the regions that will develop its region into a smart city with the concepts of smart governance, smart branding, smart economy, smart living, smart society, and smart environment. The research method used is qualitative descriptive with data sources obtained from literature studies, observations and interviews. The results of this study show that the North Penajam Paser Government is one of the regions that will build a smart city through the preparation of a master plan and KLHS by referring to the 2024 Work Plan. Smart city in Penajam Paser Utara will build a city concept that can be integrated with a touch of technology to be ready to become a smart city supported by the capabilities and potential of the region.

In broader terms, a Smart City improves the quality of life of its citizens through the effective use of innovative (digital) solutions. While innovative Smart City solutions keep growing, attention has been paid to resilience-making within Smart Cities, recognising that disasters are unavoidable. In light of the characteristics of a Smart City (smartness requirements) being inchoate and vague, different Smart Cities develop their own smartness criteria. Regardless of the Smart City type, smartness criteria need to adequately embed resilience. Integrating the resilience concept provides a strategic direction for Smart Cities and there is a significant positive relationship between the two concepts, Smart Cities, and urban resilience. Although Smart Cities are increasingly growing in popularity all around the world, there is a lack of research to guide a Smart City to define its smartness reflecting on disaster resilience. This paper intends to address this research gap by setting out a set of smartness criteria (with particular reference to urban (city) resilience) which should compulsorily feature in any type of Smart City that desires to be resilient. The study undertakes a systematic literature review to provide a new dimension, depth, and value to existing research discoveries. The findings are presented by structuring ten urban (city) resilience dimensions built upon six Smart City dimensions: smart economy, smart governance, smart people, smart mobility, smart living, and smart environment. Our findings make a niche contribution to knowledge by guiding Smart Cities that intend to build, enhance, and/or sustain resilience, to develop smartness criteria/smart characteristics reflecting on urban resilience. The research outcomes will be of large importance to Smart City policymakers, administrators, project managers, etc. to efficiently manage extreme events timely with optimal resource allocation and will be of specific interest to all the stakeholders (for instance, the innovators) in a Smart City ecosystem who may use the research outcomes as a decision-making tool.

Environmental care character is an attitude and action that always seeks to prevent damage to the surrounding natural environment and develop efforts to repair natural damage that has occurred. The character of environmental care is very important for the development of the environment and the attitude of students from an early age. Which means that the cultivation of this character must be owned by the community, especially children and introduced early in a better direction, starting from simple positive things, especially in disaster-prone environments. There are 6 indicators of planting the character of environmental care, namely cleaning toilets, cleaning trash cans, cleaning the school environment, beautifying classes and schools with plants, participating in maintaining plants in the school yard and the last behavior indicator is participating in activities to keep the environment clean. This activity aims to motivate and increase students' awareness and sensitivity activities at school in order to maintain and preserve environmental cleanliness.

This study aimed to explore Turkish elementary school students’ the views about environmental pollution at school. In this study, a phenomenological research design from the qualitative research methods was used. Study group included a total of 60 students studying in the 2-4th grades of a state elementary school in Balıkesir in Turkey. Environmental Pollution Form was used in data collection. Content analysis technique was used in data analysis. The student answers to each question were analyzed under code and category. According to study results, the students explained the concept of environment with natural beauties such as nature, forest, mountain, sea, soil, and they stated that the environment consisted of living and non-living beings. They mentioned that environmental pollution included soil, air, and water pollution, and they mostly associated environmental pollution with garbage, chemicals, fumes, and bad smells. They saw people as the reason for this. Most of the students described the environment in their school as dirty. The students did not obey the rules, environmental awareness was not developed enough in the students, garbage was thrown on the ground, the school servants did not clean the school well enough, etc. could be said among the reasons for this. It has been observed that the students used trash cans to prevent environmental pollution in their schools and warned people who threw garbage in the environment. They emphasized that the school administration and the teachers also took the necessary precautions in this regard, but that the students should be more sensitive about this issue and the school servants should clean their surroundings more. They suggested that the number of recycling bins should be increased and penal sanctions on those who litter when necessary should be imposed. The students stated that resources should be used sparingly since they are limited, which could also help prevent environmental pollution.

Kentlerde nüfus yoğunluğunun artışından kaynaklı ortaya çıkan (ekonomik, sosyal, kültürel, mekânsal, çevresel, politik) sorunlara çözüm üretmek, insanların yaşam kalitesini artırmak, sürdürülebilir büyümeyi sağlamak, işleri zamandan ve mekândan bağımsız olarak verimli ve etkin yürütmek gibi beklentilere cevap vermek amacıyla akıllı kent kavramı gündeme gelmiştir. Çalışmada akıllı kent konusuyla ilgilenen okuyuculara ve araştırmacılara yol gösterici olması amacıyla düzenli bir bibliyografya sunulması hedeflenmiştir. Çalışmada, nicel araştırma desenlerinden betimsel tarama (descriptive review) yöntemi kullanılmıştır. 2012-2020 yılları arasında akıllı kent konusuyla ilgili YÖK Ulusal Tez Merkezi internet sayfasında “Tarama” arayüzünde yer alan “Gelişmiş Tarama” bölümünden tez adında “akıllı kent”, “akıllı şehir” ve, “smart city” anahtar kelimeleriyle tarama yapılarak ilgili yüksek lisans ve doktora tezleri tespit edilmiştir. Tarama neticesinde akıllı kent, akıllı şehir, smart city anahtar kelimelerinde toplamda 75 lisansüstü teze ulaşılmıştır. Bu tezlerden 69 tanesi yüksek lisans, 6 tanesi doktora düzeyindedir. Çalışma kapsamında bu tezlerin yayınlandığı yıl, araştırma yöntemi, yazım dili, yazıldığı üniversite, yazıldığı üniversiteni türü, yapıldığı alan anabilim dalı, yazıldığı enstitü ve danışmanın akademik derecesi dahil olmak üzere 8 farklı başlıkta incelenerek değerlendirmeler yapılmıştır. Son yıllarda teknolojik gelişmelerin hız kazanmasına paralel olarak, akıllı kent konusunda yazılmış lisansüstü tezlerde de 2017 yılından sonra hızlı bir artış görülmüştür. Tezler kamu üniversitelerinde yoğunlaşırken, yazım dili olarak Türkçe dili tercih edilmiştir.