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Forklift trucks are essential tools for manual pallet handling. Storage heights at high rack storage areas often reach up to 12 meters in which bulky Cargo can hide the view of forklift operator. Pallet recognition is afundamental issue for Industries & warehouses, Particularly, a pallet recognition approach is presented to recognize pallets in the warehouses, based on calculating the degree of similarity at each location of the palette. Once a pallet has been recognized, it is matched that data with stored data. Transporting and handling pallets in a storage area is the essential function of a forklift truck. The view of the forklift truck driver is limited during his work by the lift pole, the fork, and the roof of the forklift truck. If a pallet is loaded the view is additionally hindered by its load. When the storage rack is not at a ground level or near to it the pallet handling becomes more difficult because of the distance between the forklift truck driver and the storage rack. To support the forklift truck driver during his work, there is need to advance theforklifts with different technologies and systems which provide diversity in Working and safety, security for forklift operator and other workers. This paper shows various results from research on different pallet recognition and forklift operation systems.

In this paper a Raspberry Pi based automated solution system focused on the real-time face monitoring of people to detect both face masks and body temperature with the help of MLX90614 sensor has been proposed. This is implemented using Python Programming with OpenCV Library, TensorFlow, Dlib Module. A security clearance system is deployed that will allow that person to enter if they are wearing a face mask and their body temperature is in check with WHO guidelines. A programmed hand sanitizer apportioning machine is mechanized, non-contact, liquor-based hand sanitizer gadget. Liquor is essentially a dissolvable, and furthermore a generally excellent sanitizer when contrasted with fluid cleanser or strong cleanser, likewise it needn't bother with water to wash off since it is unpredictable furthermore, disintegrates in a split second after application to hands. It is too demonstrated that a convergence of >70% liquor can execute Covid in hands. Here, we have used IR sensor detects the hand put close to which detectsthe distance and the outcome isthe pump starts running out the hand sanitizer.Thus, the above said system will help the society by saving time and also helps in contaminating the spread of coronavirus. This can be implemented in public places such as colleges, schools, offices, shopping malls, etc. to inspect people. Keywords: Deep Learning, Open CV, Keras, Python, Tensor Flow, Computer Vision, Raspberry Pi, COVID-19, DLib, Sensor, Sanitizer, Infrared sensor.

LiDAR, typically used as an acronym for “’light detection and ranging’”, is essentially a sonar that uses pulsed laser waves to map the distance to surrounding objects. It is used by a large number of autonomous vehicles to navigate environments in real time. Its advantages include impressively accurate depth perception, which allows LiDAR to know the distance to an object to within a few centimetres, up to 60 metres away. It’s also highly suitable for 3D mapping, which means returning vehicles can then navigate the environment predictably —a significant benefit for most self-driving technologies. One of the key strengths of LiDAR is the number of areas that show potential for improvement. These include solid-state sensors, which could reduce its cost tenfold, sensor range increases of up to 200m, and 4-dimensional LiDAR, which senses the velocity of an object as well as its position in 3-D space. However, despite these exciting advances, LiDAR is still hindered by a key factor; its significant cost. LiDAR is not the only self-driving detection technology, with cameras as the major rival, championed by Tesla as the best way forward. Elon Musk has described LiDAR as “a fool’s errand” and “unnecessary”. The argument runs that humans drive based only on ambient visible light, so robots should equally be able to. A camera is significantly smaller and cheaper than LiDAR (although more of them are needed), and has the advantage of seeing in better resolution and in colour, meaning it can read traffic lights and signs. However, cameras have a wide host of characteristics that make them tricky to use in common driving conditions. Whereas LiDAR uses near infra-red light, cameras use visible light, and are thus more susceptible to issues when faced with rain, fog, or even some textures. In addition, LiDARs do not depend on ambient light, generating their own light pulses, whereas cameras are more sensitive to sudden light changes, direct sunlight and even raindrops

In this article, a standalone solar tracking system is intended and successfully synchronized using proteus 7.6 ISIS. Best at instantly aligning a solar panel with the position of the sun, resulting in a 40% increase in efficiency. A low-cost solar tracking detector is being used to rotate the solar panel paired to the motor at such a specific angle to rotate 180°s in 8 steps per day with better accuracy. A microcontroller (Atmega3285P) is used as a control unit, and ADC ports are used to interconnect sensor units. To interconnect a solar array, the motor driver ULN 293D is also used to rotate the solar panel at the highest solar power angle. The modeling is performed in two ways, using four LDRs and eight LDRs, and the results of both are measured. The simulation and analysis results show that the maximum current drawn by the solar tracking sensor is less than 0.5 mA. “Proteus 7.6 ISIS” and “Arduino UNO” and “Code Vision AVR” are used to write the program code and to burn over Atmega3285P for parameters estimation.

Students’ life can be stressful and for some, it may cause mental distress. Besides being a major public health challenge, mental distress can influence academic achievements. The main objective of the current study was to examine college students for their mental health and come up with constructive solutions. Today’s younger generation represents the largest group of students. The transition from adolescence into young adulthood involves major changes in several areas- social, emotional, psychological, financial, and relationships. And this transition period can cause rational challenges that some teenagers experience stressful. It has also been mentioned that the proportion of students who experience their student life mentally stressful is increasing and for some, it may be a direct cause for mental illness. The paper focuses on how mental illness can affect one’s intellect and create barriers for their overall development. This paper includes a doctrinal method where we have surveyed 100 university students via a questionnaire. Depression, anxiety, and stress have been shown to be correlated to poor academic performances signifying a self-perpetuating disadvantage of students suffers from these mental health issues. We have also put light on how students can overcome these evils of recent times. Some solutions include awareness programs, healthy discussions with elders, exercising, and yoga for patience and calmness.

Heavy metals (HMs) and radionuclides are released through geological and anthropogenic activities and enter the environment through wastewater, soil and sediment. Large amounts of Pb (>1000 ppm), Zn (>4000 ppm) and Cd (40-400 ppm) have recently been reported in soils near Picher, USA that are harmful to the living organism. These inorganic pollutants cannot be degraded and cause damage to vital human organs and ecosystems. Different industrial and municipal solid waste was a major source of HMs in soil, including airborne aerosols. In the same manner, nuclear waste and radioactive materials used (e.g., medical facilities) or released in different processes contribute to the environmental pollution of radionuclides. The release of such toxic ions from different sources leads to mutagenesis, carcinogenesis and serious risks to the living organisms. As a result, proper management of waste from these sources, as well as environmentally friendly remediation methods, is warranted. However, recent studies have shown that it is more difficult to remove HMs and radionuclides from the source, but they can be effectively neutralized or converted into a less toxic metabolites. The combination of a unique plant-microbe system plays a key role in the remediation process. However, new bioremediation methods are now being used to eliminate HMs and radionuclides. Microbes are capable of bio-transforming, bio-sorbent and biomineralizing HMs and radionuclides through their inherent catabolic process. Enhancing phytoremediation using different strategies for the remediation of HMs and radionucleotides is necessary to ensure that the land resource is safe, fertile and productive for sustainable use.

Highlights • Electron transfer mechanism elaborated for various fungal species. • Application of fungi as a cathode and anode catalyst is discussed. • Different factors affecting on performance of fungi based MES are reviewed. • Fungi are classified based on their electron transfer mechanism., Microbial fuel cells (MFCs) that generate bioelectricity from biodegradable waste have received considerable attention from biologists. Fungi play a significant role as both anodic and cathodic catalysts in MFCs. Saccharomyces cerevisiae is a fungus with an ability to transfer electrons through mediators such as methylene blue (MB), neutral red (NR) or even without a mediator. This unique role of fungal cells in exocellular electron transfer (EET) and their interactions with electrodes hold a lot of promise in areas such as wastewater treatment where yeast cell-based MFCs can be used. The present article highlights the physico-chemical factors affecting the performance of fungal-mediated MFCs in terms of power output and degradation of organic pollutants, along with the challenges associated with fungal MFCs. In addition, to this comparative assessment of fungal-mediated bio-electrochemical systems, their development, possible applications and potential challenges are also discussed., Graphical abstract Image, graphical abstract

Population explosion and rapid industrialization have led to increase in concentration of pollutants posing threat to the environment. Therefore, it is essential to detect and reduce the level of pollutants, to conserve our natural habitat and protect the environment from further degradation. Biosensors offer a solution as analytical devices that can be customized to detect a variety of pollutants. It comprises of three essential parts—bioreceptor, transducer, and data transfer and processing. The biosensing devices have a biological component: the bioreceptor, which is biological in origin and may comprise of whole cells, cell-based receptors, enzymes, antibodies, or nucleic acids. These biological components provide advantages like detection of pollutant in low amounts, high specificity, and precision. This chapter focuses on biosensors, their types, and principles as well as recent advancements in the field.

Objective: 1. To investigate the effect of neuromuscular electrical stimulation verses electrical stimulation on gait parameters in subjects having plantar fasciitis 2. To investigate the ratio of the effect in both males and females. 3. To compare the effect of neuromuscular electrical stimulation verses electrical stimulation on gait parameters in subjects having plantar fascitis Method: Total 30 subjects were selected according to inclusion and exclusion criteria aged between 40 to 60 years. The outcome measures were foot and ankle ability measures scale, gait parameters - stride length, step length and cadence. The subjects were divided into two groups,group A was treated with Electrical Stimulation and group B with Neuromuscular Electrical Stimulation. Result: The result was extremely significant within the group on foot and ankle ability measured scale and gait parameters post 4 weeks for Group A. The neuromuscular electrical stimulation on gait parameter in individual having plantar fasciitis there result was extremely significant (p=?0.0001) post 4 weeks for Group B. Between the group comparison: Post test there was significant difference between outcome variables in FAAM (p=?0.001) and gait parameters. Following are the p values which lead to analysis of improvement in stride length (0.0021), step length (0.0378) and cadence (p=?0.001). The result from the statistical analysis of present study support the null hypothesis is rejected which stated that there will be beneficial effect to the subject treated with neuromuscular stimulation than electrical stimulation Conclusion: Based on the statistical results and interpretation it was concluded that Neuromuscular electrical stimulation showed reduction in pain and improvement in gait parameters in individual having plantar fasciitis. Both the groups showed significant results but, post intervention Neuromuscular electrical stimulation group showed extremely significant effect than the electrical stimulation group