There is an acute shortage of human coconut tree climbers to harvest coconuts in India and other developing countries. The consequential diminished availability of skilled tree-climbers, to pass along the trade secrets to the succeeding generations, highlights the exigent need for an unmanned coconut-tree-climber as an alternative solution. This research presents Amaran, a novel robotic coconut tree climber and harvester. Amaran is comprised of a harvester with a distinctive robotic arm (RA) and a cutter, which can be attached to a ring-shaped frame that can be fastened to a coconut tree. Amaran can be controlled, through a wireless interface, either by an operator on the ground or via a smartphone-based app. Once dispositioned in the vicinity of the coconut bunch, the cutter is commanded to harvest the coconuts, by cutting the stem of the bunch attached to the tree. Verification of the Amaran robot's viability was confirmed by tests conducted on a coconut tree setup in the design lab. Subsequently, the design of the Amaran robot was validated by field tests in a coconut farm. In this paper, we discuss the design of the Amaran body and the harvester. Amaran's dexterity in climbing and harvesting coconuts can be challenged by height, circumference, and inclination of the tree. Experimental results show that Amaran can successfully climb trees up to 15.2 m tall, of circumferences ranging from 0.66 m to 0.92 m, and tree trunk inclinations of up to 30 degrees.

IoT-based wearable devices are significantly contributing to personalized and pervasive modern healthcare. Traditional healthcare systems are handicapped by several factors, including shortages of physicians, nurses, healthcare devices, hospital beds, healthcare cost, etc. Conventional therapy is carried out either at a hospital or at home by certified therapists which is not affordable for many in developing nations. In this research work, we present IoT-based monitoring and an evaluation of key parameters and indicators of a wearable device used during the rehabilitation process in stroke patients’ hand therapy which can be operated by the users at home without the need for therapists. Sensors along with a controller board are used for signal acquisition, processing, and monitoring. The efficiency of therapy can be increased through real-time follow-up and feedback from therapists. Three different control methods are proposed and studied: smartphone-based speech, smartphone-based touch, and Internet of Things (IoT)-based dashboard. In addition, four different architectures, including: therapist therapy wearable, dual therapy wearable, user therapy wearable, and multiuser therapy wearable architectures are discussed. A rehabilitation therapy-based case study using the proposed wearable device with multiple volunteers was conducted. Therapists can remotely operate the device and train the users. Users can benefit and save on costs without the need to visit hospitals or therapy centers or hire therapists. Based on the results of the experiments with volunteers, we can confidently say that the proposed IoT-based wearable device can enhance the quality of life and well-being of the users.

Many accidents happen while driving due to false estimation of the tailgating vehicle's distance and even while backing up or parking the vehicles in a parking lot. It is very important for the driver to know how close the tailgating vehicle. It is equally important to know the vicinity of the other vehicles and objects while parking or taking vehicle from the parking lots. The main objective of this paper is to accurately estimate the distance of a specific object by approximating the camera to be an ideal pinhole camera. In this method we use triangle similarity to estimate the distance after obtaining the focal length (in pixels) of the camera. Using image processing techniques we detect the object for which we want to estimate the distance. We input the known width of the object and using the calculated focal length, the algorithm calculates the distance after identifying the object. The experimental results are very promising that the estimation of the distance of an object using pin hole approximation would be extremely useful in vehicles to avoid accidents.

This paper presents a novel and simple hand gesture recognition method to be used in rehabilitation of people who have mobility issues particularly stroke patients and patients with spinal cord injury (SCI). Keeping in mind the reach of such a system for a wider community of people with mobility issues, the proposed low-cost control device called gpaD-gesture pad provides an alternative solution to the joystick-based powered wheelchair control through hand gestures. In this method, IR sensors are used for identifying the simple gestures to control the powered wheelchair to move in any direction. In the proposed prototype system HanGes, a gesture pad that includes IR sensors, MCU and power management circuit is designed for gesture recognition and identification and a controller for driving motors is implemented. HanGes's design, implementation, the response time calculations of the system, testing, performance evaluation with stroke and SCI patients are discussed in detail. With the average success rate of gesture recognition above 99.25% and response time as comparable with that of commercially available joystick controlled wheelchair, HanGes could be a possible alternative to the existing ones. With extensive experiments that demonstrate the accuracy of the system, the user experience, testing with patients, and the implementation cost indicate the superiority of our system.