Since the term of a smart city was proposed, Internet of Things (IoT) has been considered as the infrastructure’s key in a smart city. Huge research consideration is an emphasis on remote wellbeing observing system dependent on IoT technology. IoT is the internetwork of physical objects or “things” that are embedded with software and sensors to collect and send data between them and central servers with minimum human intervention. This term can assist decline with constraining on medical clinic system and healthcare suppliers, decrease insurance costs, and improve healthcare. In the modern healthcare environment, IoT is being used in various medical areas like real-time monitoring, patient information management, medical emergency management and blood information management. Over these years a number of advanced applications based on IoT have been proposed for convenience of patients, doctors and caregivers in the healthcare sector. Therefore, the current study describes the applications of IoT technologies in medical and healthcare field. Moreover, the it highlights the huge potential of this process and future directions for further research.

This study aims to evaluate the 3D-printed parts of different materials in terms of the achieved mechanical properties and surface characteristics. Fourteen infill patterns were employed in the 3D printing of polylactic acid (PLA), enhanced polylactic acid (PLA+), and polyethylene terephthalate glycol (PETG) materials. The printed specimens’ mechanical properties and surface characteristics were evaluated and discussed. Ultimate tensile strengths, Young’s modulus, and strain at break % were determined as mechanical properties, while average, maximum, and total height of profiles (Ra, Rz, and Rt) were measured as surface characteristics of the produced specimens. The cubic, gyroid, and concentric patterns were found to be the best infill patterns in terms of the mechanical properties of PLA, PLA+, and PETG materials, where maximum ultimate tensile strengths were recorded for these materials: 15.6250, 20.8333, and 16.5483 MPa, respectively. From the other side, the best Ra, Rz, and Rt were achieved with cross, quarter cubic, and concentric patterns of the PLA, PETG, and PLA+ materials, where the best values were (2.832 µm, 8.19 µm, and 17.53), (4.759 µm, 24.113 µm, and 35.216), and (4.234 µm, 30.136 µm, and 31.896), respectively.

The issue of water logging due to plastic, thermocole and metal is prompting bother development and it favors ailments like intestinal sickness, typhoid and so on. Cleaning the wastes by utilizing manual procedures would be insufficient as it regularly covers immense territory of works and endeavors with plausibility to getting influenced by different sicknesses from the irresistible microorganisms present in the sewage while cleaning manually. This study features a proposed plan of garbage gathering system viable and effective for tidying up waste from rivers, channels and lakes. The trash gathering system is explicitly coordinated to application for getting up a wide assortment of debris, including gliding litter, trash, logs, disposed tires and others. The integrated system incorporates the usage of IoT technology that has the ability to monitor and control the entire process. From the interest and need of cleaning contaminations in the conduits territory, the vessel has been created to suit the prerequisite of working at places other than seaward zone, giving more decisions for the utilization of cleaning garbage and waste from the water environment.

In recent years the trends were towards modeling of machining using artificial intelligence. ANN is considered one of the important methods of artificial intelligence in the modeling of nonlinear problems like machining processes. Artificial neural networks show good capability in prediction and optimization of machining processes compared with traditional methods. In view of the importance of artificial neural networks in machining, this paper is an attempt to review the previous studies and investigations on the application of artificial neural networks in the milling process for the last decade.

Recently, there is a growing demand towards adopting 3D printing technology in various sectors due to its potential merits. The mechanical properties and surface quality of the final product are influenced by the process parameters. Therefore, this study aims to optimize the infill density and pattern beside printing speed and temperature to achieve optimum mechanical properties and surface characteristics of PLA+ 3D-printed material. The Taguchi method was applied with L9 array, and tensile and surface roughness tests were carried out to evaluate the performance of specimens in terms of the obtained ultimate tensile strength, Youngs modulus, tensile strain (), and surface roughness. The selected parameters with their levels were as follows: printing temperature (205, 215, and 225°C), printing speed (20, 50, and 80mm/s), infill density (30, 60, and 90), and infill pattern (triangle, cubic, and concentric). The findings revealed the significant impact of the infill density followed by the infill pattern on the mechanical and surface performances of the PLA+ material. From the other side, the Taguchi method was integrated with grey relational analysis (GRA) as a multiobjective optimization to find out the optimum mechanical properties and surface characteristics of the 3D-printed PLA+ part. Accordingly, 215°C, 50mm/s, 90, and triangle pattern achieved optimum mechanical properties (24MPa, 3.14GPa, and 13.72) and surface roughness (3.21µm).

Solar energy, being a noteworthy wellspring of sustainable power source, is significant in satisfying future energy need. To ensure efficient operation of photovoltaic panels, it is fundamental that the system presents proper cleaning operation to all obstructed materials that may impede the solar light-based radiation. The amassing of dirt or particles like residue, water, sand and greenery on the outer surface of the solar-based photovoltaic panel deter or divert light vitality from achieving the solar oriented cells. This is a noteworthy issue since the light obstruction materials play as resistance that diminishes the performance of solar photovoltaic. The target of this study is to delineate innovation of robotics technology for cleaning photovoltaic boards. The proposed strategy screens the power generation and cleans the photovoltaic surface when required progressively on mobile app. The enhancements accomplished by the unique structure and the created model confirmed the common sense of the proposed design.