Ambient Assisted Working (AAW) is a discipline aiming to provide comfort and safety in the workplace through customization and technology. Workers’ comfort may be compromised in many labor situations, including those depending on environmental conditions, like extremely hot weather conduces to heat stress. Occupational heat stress (OHS) happens when a worker is in an uninterrupted physical activity and in a hot environment. OHS can produce strain on the body, which leads to discomfort and eventually to heat illness and even death. Related ISO standards contain methods to estimate OHS and to ensure the safety and health of workers, but they are subjective, impersonal, performed a posteriori and even invasive. This paper focuses on the design and development of real-time personalized monitoring for a more effective and objective estimation of OHS, taking into account the individual user profile, fusing data from environmental and unobtrusive body sensors. Formulas employed in this work were taken from different domains and joined in the method that we propose. It is based on calculations that enable continuous surveillance of physical activity performance in a comfortable and healthy manner. In this proposal, we found that OHS can be estimated by satisfying the following criteria: objective, personalized, in situ, in real time, just in time and in an unobtrusive way. This enables timely notice for workers to make decisions based on objective information to control OHS.

In this paper, a sensor network architecture is presented. This work proposes an early warning system for river overflows. The sensor network consists of a river level sensor node that measures the distance between the sensor and the mass of water using a precision ultrasonic sensor. The recorded information is transmitted to a receiving node by radio frequency (915 MHz) using LoRa modulation. The receiving node is implemented in a Raspberry Pi, it processes the information in real time and publishes the alert using a social network (Twitter). Finally, a prototype of the river level node was tested, obtaining a measurement range from 20 cm to 2 m. The receiving node was located 500 m away from the sensor node, that received the data packets sent without loss of data.

Social networks are useful tools for disseminating emergency warnings of danger to the population since it promises enormous success because most of the citizens have mobile phones with Internet and social networking applications. We can take advantage of designing a river level sensor to monitor in real time the water level of the river, in addition to storing historical data to forecast leveling or possible overflowing of rivers, it allows citizens to have an early warning system to be informed promptly and power make a decision before disaster strikes. The dissemination of information and deploying devices enabled by IoT (Internet of Things) could bring benefits in terms of giving to people information opportunely for making decisions in the face of this disaster. In this paper, we present a sensor to measure water level in rivers. We designed a pilot project through a water level measurement sensor based on an ultrasonic sensor, this sensor detects objects (water) by emitting a short ultrasonic burst and then listening for the echo, it calculates the distance between the sensor and the body of water. All data collected from the water level sensor are transmitted to a server. After social networks users such as Facebook can know the water level in rivers.

Choosing a routing protocol is an essential part in the success of the communication in mobile Ad-Hoc networks (MANET), since their topology is constantly changing. In many MANET applications (such as rescue tasks applications) it is necessary to assure reliable communication among network nodes. In this paper is showed a performance evaluation of two reactive routing protocols in order to know which is the most appropriate one for rescue tasks operations. Two protocols are evaluated: AODV (Ad hoc On Demand Distance Vector) and DYMO (Dynamic MANET On-demand routing protocol). Various mobility conditions in the environment are presented as well as the respective behavior of the protocols under these variations. The results of this work are organized in metrics which enabled the conclusions about the protocols performance.

This paper proposes an experimental design to publish online the measurements obtained from four sensors: one sensor inside a cistern measures the level of drinking water, another sensor in a water tank monitors its level, a third sensor measures water flow or pressure from the pipes, and a fourth sensor assesses water quality. Several tank filling and emptying tests were performed. Experimental results demonstrated that if the cistern perceived that there was no water in the tank, it turned on the water pump to fill the tank to 100% of its storage capacity; while this was happening, the water level in the cistern and tank, the flow of water from the piped water, and the quality of the water could be visualized on a dashboard. In short, this proposal monitors water levels and flows through the Internet of Things. Data collected by sensors are posted online and stored in a database.