Arco Innovation Award
Arco Innovation Award: Meet the finalists, part 2
The second batch of Arco Innovation Award finalists, in the ergonomics and wearable technology categories, has been announced.
Launched in October, the Arco Innovation Award aims to drive innovation in the health and safety sector. The finalists have been split into categories. See the first batch of Arco Innovation Award finalists, in the Software & AI solutions and AR, VR & MR categories, here. The second batch of nine are previewed below. Click here to view the final batch of finalists, in the Robots and Cobots, Drones and Proximity Detection categories.
A risk-prevention analytics solution known as KIMEA. It assesses the ergonomics of workers movements when performing manual tasks. Using a specialised depth camera and sensing gloves to capture data from a gesture which is then replicated digitally and processed by proprietary algorithms to evaluate the person’s risk of causing musculoskeletal disorders. The solution can be applied to educate employees in a number of sectors, such as food production and processing and manufacturing decreasing the chance of workplace injury.
A smart back sensor and connected mobile phone app to help those with back pain. A wearable device, which can be attached to the user’s clothing, it combines position and movement analysis with real time interaction and training and provides constant feedback on the user’s posture.
The system is used by numerous individuals, from athletes to office workers.
A software to identify bad posture in a working environment. It aims to reduce and prevent musculoskeletal disorders developed in the workplace. Using a camera to record footage of workers undertaking daily activities, the software creates a virtual double of the worker, which illustrates any potentially harmful or painful movements, allowing companies to take corrective action. The movement data can also be used for ergonomics training, reducing employee risk and improving workplace safety.
An automated analytics tool for manual logistics processes. It collects data about worker ergonomics, productivity and efficiency, using machine learning algorithms and wearable sensors that detect movement and activity. MotionMiners then uses this data to analyse manual work processes to detect the cause of potential flaws in logistics processes. It also promotes greater safety in the working environment, through the monitoring of workers’ movements.
Wireless headsets that provide hearing protection and noise monitoring. Eave headsets also contain microphones, allowing for on-site worker communications and sound recording. The headsets automatically monitor and log noise data, which is then instantly transferred to ‘Peak’, a data platform that can be accessed via a web browser. The Peak platform automatically creates noise maps, which highlight noise exposure across a site and how it changes over time. The solution aims to reduce the risk of workers developing noise-related hearing loss and promotes greater environmental awareness by employees.
A smart-phone application for lone worker safety. It is a tracking application, generally utilised by businesses with isolated workers, such as technicians and security officers.
The application automatically detects the movement and physical positioning of its user and sends an alert to the employer in the event of an accident. The user can also manually send alerts themselves.
Eyewear with embedded sensors that detect the loss of attention of the wearer using artificial intelligence.
The glasses are paired with a smartphone application which creates and stores information about the wearer’s general health. The solution can also be adapted to fit the needs of companies through the Fleet Manager application. This application enables the data of multiple wearers – such as within a fleet – to be collected and stored in a single location. In future, the plan is to apply this technology to other health use cases, such as helping to prevent a heart attack or diabetic crisis.
A wearable, hands-free remote that allows the user to control overhead cranes. The remote, ‘ComHand’, is a bracelet which can be worn on either wrist. The device detects the directional movements of the wearer and automatically sends instructions to the crane. The hands-free control increases safety by reducing the risk of contact-induced injury and also promotes greater productivity, due to the user maintaining control of both hands.
A producer of collaborative robots and exoskeletons which are designed for handling heavy loads safely and ergonomically. Targeting heavy industry by offering collaborative robots that can assist operators in their work, it reduces potential risks and worker arduousness. Its exoskeleton, ‘Hercules’, can assist a person walking with heavy loads on their back without the risk of injury. Its technology can support sectors such as food, mechanical, aerospace and defence.