The value of total coliforms, faecal coliforms and faecal streptococci in predicting the presence of Salmonella spp. and the numbers of Staphylococcus aureus and Candida albicans in sewage polluted coastal water were assessed. All indicators had strong positive association with Salmonella and moderate positive correlations with Staph. aureus and C. albicans. Total coliforms correlated better with salmonellas and Staph. aureus than did the two faecal groups. Regression analysis revealed that total coliforms have a better value as predictors of the presence of Salmonella and Staph. aureus, while faecal coliforms are better predictors of C. albicans, in moderately polluted areas. The conclusion reached is that enumeration of total coliforms is sufficient to predict the presence of Salmonella spp. or Staph. aureus in sea water moderately affected by sewage pollution, without the additional measurement of faecal coliforms and faecal streptococci.

Many workers operate in environments that are inherently hazardous and that are subject to strict health and safety rules and regulations. We envisage a world in which physical work artefacts such as tools, are augmented with intelligent mobile nodes that are able to observe the working activities taking place, evaluate compliance with health and safety regulations and assist or actively enforce compliance with these regulations. This vision creates a new field of work in the area of health and safety aware intelligent mobile sensor networks. In this paper we describe a number of new challenges faced when developing mobile systems for compliance with health and safety regulations.