In Wireless Sensor Networks (WSN) sensor nodes with sensing, computing and communication infrastructure are randomly deployed and organized as clusters. Most of the existing sensor networks focus on homogeneous in which the cluster heads are changed periodically. To improve the lifetime of energy constraint battery powered WSN and to avoid energy sink-hole problem; Clustered Heterogeneous Sensor Networks (HSN) are analyzed with mobile sink. Our proposed method combines load balanced clustering, transmission power control over normal nodes present in the cluster and mobile sink over HSN. PSO is used to find the optimal path for mobile sink to collect data from cluster heads. The experimental results show that the proposed system has lower energy consumption and improved lifetime over static sink, without load balancing and power control approaches. The optimal path algorithm based on PSO is more robust and easy to reach the solution for real world environmental monitoring and data aggregation problems

Internet of things (IoT) will be the main part in upcoming generation devices that would not simply sense and report, also will have the controlling capability. It may be a connected vehicle, connected devices, robot, a building automation system, a door lock or a thermostat, these connected machines or devices will provide greater impact on our daily lives. Control data and the operating instructions could be protected to ensure control and autonomy for our safety and security, this could be a critical task. Privacy and security are important consideration in designing the system. With the intense growth of devices or devices with facilities such as computing and communication are carried out using a profound technology known as machine to machine (M2M) communication, which is specially designed for cross‐platform integration. In many industries, smart homes, smart cities, smart agriculture, government, connected devices, security, healthcare, education, public safety, and supply chain management. Internet of things (IoT) and machine to machine communication have to be implemented in near future. Also, this paper gives an in depth view about the different M2M techniques with interconnected IoT for truly connected, smart, and sustainable world.

The problem of denoising iris pictures for iris identification systems will be discussed, as well as a novel solution based on wavelet and median filters. Different salt and pepper extraction algorithms, as well as Gaussian and speckle noises, were used. Because diverse sounds decrease picture quality during image collection, noise reduction is even more important. To reduce sounds like salt and pepper, Gaussian, and speckle, filtering (median, wiener, bilateral, and Gaussian) and wavelet transform are utilised. Provide better results as compared to other ways. A study of several efficiency indicators such as peak signal-to-noise ratio (PSNR) and mean squared error will be used to demonstrate the superiority of the proposed technique (MSE).

The advanced technology for synthesizing nanoparticles utilizes natural resources in an environmentally friendly manner. Additionally, green synthesis is preferred to chemical and physical synthesis because it takes less time and effort. The green synthesis of cobalt oxide nanoparticles has recently risen due to its physico-chemical properties. In this study, many functional groups present in Psidium guajava leaf extracts are used to stabilize the synthesis of cobalt oxide nanoparticles. The biosynthesized cobalt oxide nanoparticles were investigated using UV-visible spectroscopic analysis. Additionally, Fourier-transform infrared spectroscopy revealed the presence of carboxylic acids, hydroxyl groups, aromatic amines, alcohols and phenolic groups. The X-ray diffraction analysis showed various peaks ranging from 32.35 to 67.35°, and the highest intensity showed at 36.69°. The particle size ranged from 26 to 40 nm and confirmed the average particle size is 30.9 nm. The green synthesized P. guajava cobalt oxide nanoparticles contain cobalt as the major abundant element, with 42.26 wt% and 18.75 at% confirmed by the EDAX techniques. SEM images of green synthesized P. guajava cobalt oxide nanoparticles showed agglomerated and non-uniform spherical particles. The anti-bacterial activity of green synthesized P. guajava cobalt oxide nanoparticles was evaluated against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli with a 7 to 18 mm inhibitory zone. The photocatalytic activity was evaluated using green synthesized P. guajava cobalt oxide nanoparticles and observed 79% of dye degradation. The MTT assay of P. guajava cobalt oxide nanoparticles showed an excellent cytotoxic effect against MCF 7 and HCT 116 cells compared to normal cells. The percentage of cell viability of P. guajava cobalt oxide nanoparticles was observed as 90, 83, 77, 68, 61, 58 and 52% for MCF-7 cells and 82, 70, 63, 51, 43, 40, and 37% for HCT 116 cells at the concentration of 1.53, 3.06, 6.12, 12.24, 24.48, 50, and 100 μg/mL compared to control cells. These results confirmed that green synthesized P. guajava cobalt oxide nanoparticles have a potential photocatalytic and anti-bacterial activity and also reduced cell viability against MCF-7 breast cancer and HCT 116 colorectal cancer cells.

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